Adolescence is a key developmental period in which new health behaviours are often initiated that track into adulthood. In the age of digitisation, adolescents are frequently exposed to and actively seek health information from digital sources. Widespread misinformation necessitates the ability to critically evaluate the reliability of sources, a key component of digital health literacy. Digital health literacy, sometimes called e-health literacy, is considered a determinant of health. Evidence suggests an association between digital health literacy and health behaviours among adults; however, the concept has been sparsely investigated among adolescents. This protocol outlines a proposed scoping review that aims to identify, map and synthesise the currently available literature relating to the digital health literacy of adolescents. The objective of the proposed scoping review is to understand the extent, breadth and type of evidence available regarding the digital health literacy or e-health literacy of adolescents. A scoping review of literature will be conducted in accordance with the methodological framework proposed by Arksey and O'Malley, with refinements suggested by Levac et al and guided by the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis. Reporting will follow the Preferred Reporting Items for Systematic Reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR). Searches for relevant studies have been conducted across five electronic databases (PubMed, CINAHL, Web of Science, Education Source and Scopus). Title and abstract screening, which has commenced, will be conducted primarily by the lead reviewer, with independent verification of a subset of records to enhance rigour and minimise selection bias. This will be followed by full text screening using Covidence software. The PCC (Population, Concept and Context) framework guided the development of the inclusion and exclusion criteria for study selection. A manual search of references of included studies will be conducted to identify further studies for inclusion. Data will be extracted and analysed using a descriptive mapping approach. Published quantitative and qualitative studies exploring the digital health literacy, or e-health literacy of adolescents aged 10 to 19 years will be included. Eligible study designs include randomised controlled trials, non-randomised controlled trials, pre-post studies, prospective and retrospective cohort studies, case-control studies and analytical cross-sectional studies. This review will also consider descriptive observational study designs including case series, individual case reports and descriptive cross-sectional studies for inclusion. The proposed scoping review aims to map how digital health literacy is defined and measured among adolescents, providing greater conceptual clarity within the emerging field. By identifying patterns, inconsistencies, and gaps in the literature, the findings are expected to inform future research priorities, scale development, and the design of targeted interventions in educational and public health settings. Consistent with the scoping review methodology, a risk of bias assessment will not be conducted however the systematic approach will map the available evidence and form the basis for future research. This scoping review protocol has been preregistered on the Open Science Framework (OSF Registries, available at: https://osf.io/xsvpz/).
Gestational diabetes mellitus (GDM) is associated with fetal overgrowth, increased risks of perinatal morbidity and mortality, and long-term complications for mother and child, including cardiovascular disease and type 2 diabetes. Innovative, peer-based digital health interventions are emerging globally as a potential approach to assist and empower women in effective self-care and well-being during pregnancy. However, there remains substantial potential to develop and evaluate culturally sensitive digital health interventions for pregnant women with GDM, especially in low- and middle-income countries. This study aimed to bridge the gap between the World Health Organization (WHO) self-care framework and local practice by designing and piloting the "Healthy Pregnancy" intervention, a multiplatform digital ecosystem for women with GDM in northern Vietnam, through a staged cocreation and pilot refinement process. Between December 2022 and February 2024, drawing on the WHO's conceptual framework for self-care and cocreation approach, we iteratively developed "Healthy Pregnancy," a digital health intervention, in 4 stages: (1) formative studies and self-care construct prioritization, (2) cocreation processes with key stakeholders, (3) development and design translation, and (4) pilot testing and final refinement. In stage 1, we identified gaps in current digital health interventions in low- and middle-income countries, explored the sociocultural realities of women with GDM in Vietnam, and prioritized 7 self-care constructs. In stage 2, we conducted a cocreation workshop to enable key stakeholders to co-design the foundational infrastructure for the potential intervention. In stage 3, we established a multicomponent digital intervention ecosystem with explicitly defined operating workflows. Finally, in stage 4, we gathered suggestions for a digital health intervention from a pilot test group of pregnant women with GDM, to refine and optimize the system schematic and information flow before moving to the real intervention. By applying a cocreation approach across all stages of development of the "Healthy Pregnancy" digital health intervention, from problem identification to solution development and evaluation, we developed a locally tailored GDM self-care model. This process not only addressed gaps in standard care but also empowered pregnant women through a supportive, multiple-stakeholder environment. This study demonstrates a rigorous cocreation pathway for systematically translating WHO self-care constructs into a feasible, culturally adapted digital ecosystem for GDM in Vietnam and offers a transferable, people-centered design process alongside a practical blueprint for integration into routine maternal care.
Hearing loss affects approximately 432 million adults globally, with Deaf individuals representing a distinct linguistic and cultural minority that faces significant barriers to accessing health information. These challenges contribute to health disparities by limiting preventive education and timely health interventions. This scoping review examines the effectiveness of digital communication technologies in promoting health literacy, awareness, and health-related skills among Deaf adults and children. A comprehensive literature search was conducted across 5 major databases: MEDLINE, Embase, Scopus, Web of Science, and PubMed, focusing on peer-reviewed studies published in English within the past 10 years. Seventeen studies were included, encompassing a variety of research designs, including randomized controlled trials, cross-sectional surveys, and mixed methods approaches. Data extraction focused on intervention type, outcomes, and target populations. Findings indicate that video-based interventions are the most prevalent and effective, leveraging sign language, subtitles, and animations to enhance accessibility and comprehension. These digital tools improved health awareness, knowledge acquisition, and the practical application of health-related skills across both adult and child populations. Interventions ranged from stroke preparedness and cancer education to breast self-examination and cardiopulmonary resuscitation training. Social media platforms, SMS text messaging campaigns, and eHealth programs were also identified as effective in promoting preventive health behaviors. Despite these promising outcomes, several challenges remain, including limited digital literacy, inconsistent access to technology, and a lack of culturally and linguistically appropriate content. Additionally, most studies were geographically concentrated in the United States, with a limited number of high-quality randomized trials. This review highlights the transformative potential of accessible digital technologies to reduce health disparities and promote health equity among Deaf individuals. Future research should prioritize inclusive, culturally sensitive, and user-centered designs and explore emerging platforms to maximize engagement and improve health outcomes.
With the rapid expansion of digital technologies and the global increase in social media use, this study aimed to investigate the relationship between digital health literacy (DHL) and problematic mobile social media use (PMSMU) among adolescents, as well as the underlying mechanisms. A total of 555 adolescents were surveyed using the eHealth Literacy Scale (eHEALS), the Problematic Mobile Social Media Usage Assessment Questionnaire, the Physical Activity Rating Scale (PARS-3), and the social-emotional competence scale. DHL was significantly correlated with physical activity (PA) (r = 0.233, p < 0.001), social-emotional competence (SEC) (r = 0.133, p < 0.001), and PMSMU (r = -0.120, p < 0.001). Mediation analysis revealed three significant indirect pathways: PA mediated the relationship (21.43%), SEC mediated it (10.71%), and a sequential pathway through PA and SEC also emerged (5.36%). DHL not only directly predicts PMSMU but also indirectly predicts it through the independent and chain mediating effects of PA and SEC. Among these indirect pathways, PA emerged as the most influential mediator.
The UK Medical Research Council's Guidance on Developing and Evaluating Complex Interventions (MRC GDECI) outlines a 4-phase framework for structuring research programs on interventions: development, feasibility, evaluation, and implementation. However, it provides limited practical direction on how researchers should select which phases to conduct or determine when and whether to progress between phases. This gap is particularly challenging in the context of digital health interventions (DHIs), given their fast-paced and rapidly evolving nature. This scoping review examined the research phases conducted, how researchers progressed through them, and the intervention characteristics associated with overall program structure and duration in DHI research, to inform the design of future research programs. We searched PubMed, Embase, CINAHL, PsycINFO, and ClinicalTrials.gov to identify complex DHIs promoting health among adolescents and young adults, implemented between 2017 and 2026, for which at least 2 phases of the MRC GDECI were reported, including the evaluation phase. For each eligible intervention, all related protocols, preprints, and published articles were retrieved to reconstruct the full research program. For each program, we analyzed the presence of each research phase, its organization (ie, phase arrangements), and the mechanisms guiding progression between phases (ie, progression mechanisms). Phase-specific and overall program durations were recorded. A total of 31 research programs, covering 31 interventions and reported in 130 articles, were included. Development, feasibility, evaluation, and implementation phases were reported in 26, 23, 31, and 7 research programs, respectively. Three types of phase arrangements were identified: sequential, iterative, and overlapping. Progression mechanisms between phases included automatic progression, conditional progression based on researchers' appraisal of findings without prespecified criteria, and progression based on predefined quantitative criteria. Six main research program structures were observed, combining phase arrangements and progression mechanisms. Iterative arrangements were most common, observed in 22 research programs, followed by overlapping (n=10) and strictly sequential structures (n=7). Most progressions relied on researchers' appraisal of findings without prespecified criteria. Justifications for phase iteration, omission, or progression decisions were rarely reported. The median program duration was 5.8 (IQR 3.8-6.6) years (n=13). Based on these findings, a novel 4-step operational framework and visualization tools were developed to guide the design and planning of DHIs, highlighting key considerations for each step, as well as the strengths, limitations, and risks associated with each phase arrangement and progression mechanism. This scoping review is the first to systematically examine phase arrangements and progression mechanisms in DHI research programs. Beyond descriptive reporting, it provides a conceptualization of research program structures and offers a flexible operational framework to support the concrete implementation of the MRC GDECI. Greater explicitness in decisions about program structure may enhance methodological rigor, reduce research waste, and improve the integrity and reproducibility of interventions. PROSPERO CRD42023401979; https://tinyurl.com/mvc265y3.
More than one billion people are affected by a mental disorder according to the World Health Organization (WHO). In this context, information coverage of mental health is one of the great challenges for the media in a scenario marked by misinformation and digital noise. This work, from a transversal descriptive methodological approach, has analysed the news related to mental health in the main digital media of 20 Latin American countries. The study identifies that depression, anxiety, stress, suicide, substances and addictions, and neurocognitive disorders are the disorders with the greatest presence in news coverage. Furthermore, the work detects a moderate relationship between the variable's 'disorder' and 'relationship with violence'. On the other hand, only 25% of the information analysed raised recovery processes as a significant topic in the writing. The work also highlights that messages with interviews with experts or citations to medical studies contribute to more positive approaches in mental health coverage. Más de mil millones de personas están afectadas por un trastorno mental según la Organización Mundial de la Salud (OMS). En este contexto, la cobertura informativa de la salud mental es uno de los grandes desafíos de los medios de comunicación en un escenario marcado por la desinformación y el ruido digital. Este trabajo, desde un planteamiento metodológico descriptivo transversal, ha analizado las noticias relacionadas con la salud mental en los principales medios de comunicación digitales de 20 países de Iberoamérica. Se identifica que la depresión, la ansiedad, el estrés, el suicidio, las adicciones y los trastornos neurocognitivos son las condiciones con mayor presencia en la cobertura informativa. También se detectó una relación moderada entre las variables ‘trastorno’ y ‘relación con la violencia’. Por otro lado, solo el 25% de las informaciones analizadas planteaban los procesos de recuperación como un tema significativo en la redacción. Se destaca que las noticias con entrevistas a expertos o citas a estudios médicos contribuyen a enfoques más positivos en la cobertura de la salud mental. De acordo com a Organização Mundial da Saúde (OMS), mais de um bilhão de pessoas são afetadas por um transtorno mental. Nesse contexto, a cobertura jornalística da saúde mental é um dos grandes desafios enfrentados pela mídia em um cenário marcado pela desinformação e pelo ruído digital. Este estudo, usando uma abordagem metodológica descritiva transversal, analisou as notícias relacionadas à saúde mental nas principais mídias digitais em 20 países da América Latina. Depressão, ansiedade, estresse, suicídio, vícios e distúrbios neurocognitivos foram identificados como as condições com maior presença na cobertura jornalística. Também foi detectada uma relação moderada entre as variáveis “transtorno” e “relação com a violência”. Por outro lado, apenas 25% dos itens de notícias analisados apresentaram os processos de recuperação como um tópico significativo na cobertura jornalística. Ressalta-se que as notícias com entrevistas a especialistas ou citações de estudos médicos contribuem para abordagens mais positivas na cobertura da saúde mental.
Prior studies often examine single telehealth encounter types or aggregate all digital care, overlooking how patients combine multiple digital and in-person modalities in hybrid care. To address this gap, we derived hybrid care engagement phenotypes and assessed sociodemographic differences and associations with glycemic control among adults with type 2 diabetes (T2DM). We conducted a retrospective cohort study of 10 671 adults with T2DM receiving primary care at an academic (UCSF) or safety-net system (SFHN) from April 2021 to March 2023. K-medoids clustering was applied to five encounter modalities (in-person, video, telephone visits; portal messages; unscheduled telephone calls) to derive four engagement phenotypes. We assessed sociodemographic differences using chi-square and Kruskal-Wallis tests and evaluated associations between phenotype and follow-up HbA1c control using logistic regression. We tested interactions with baseline HbA1c and estimated predicted probabilities using Tukey-adjusted contrasts. Four phenotypes emerged per system: Digitally Engaged Multimodal, Traditional High Utilizers, Digitally Leaning (UCSF), Telephone Reliant (SFHN), and Low Digital. UCSF patients belonged to digitally forward phenotypes, whereas SFHN patients concentrated in traditional, lower-tech phenotypes. Among patients with uncontrolled diabetes, digitally forward phenotypes had 13-20 percentage points higher predicted probability of achieving control (UCSF: 56% Digitally Leaning vs 36% Traditional; SFHN: 53% Multimodal vs 40% Telephone). Phenotypes varied by health system and sociodemographic factors, with modest, system-specific associations between digitally forward phenotypes and glycemic control among patients with uncontrolled diabetes. Findings underscore structural and sociodemographic inequities in hybrid care engagement and the need for proactive, tailored strategies to promote equitable hybrid care.
Digital therapy applications offer great potential to improve the therapeutic care of patients with musculoskeletal complaints and contribute to maintaining their ability to work. The study summarizes the current status of studies on the use of digital therapy applications recognized by the pension insurance in the orthopaedic field of prevention, rehabilitation, and rehabilitation aftercare and describes their effectiveness. The review was designed as a scoping review. Quantitative outcome measures such as ability to work, health-related quality of life, or sports medicine assessments were extracted and reported. The characteristics of the studies included were compared in tabular form. Digital therapy programs were well accepted and proved to be comparably effective to traditional formats, with context-specific advantages for some outcome parameters. Digital therapies are an effective therapy format with flexibility in terms of location and time. HINTERGRUND: Digitale Therapieanwendungen bieten großes Potenzial, die therapeutische Versorgung von Patienten mit muskuloskelettalen Beschwerden zu verbessern und zum Erhalt der Erwerbsfähigkeit beizutragen. Die Arbeit fasst den aktuellen Stand der Studienlage zum Einsatz der von der Rentenversicherung anerkannten digitalen Therapieanwendungen im orthopädischen Bereich in Prävention, Rehabilitation und Reha-Nachsorge zusammen und beschreibt deren Wirksamkeit. Die Übersichtsarbeit ist als Scoping-Review angelegt. Quantitative Outcome-Messungen wie Arbeitsfähigkeit, gesundheitsbezogene Lebensqualität oder sportmedizinische Assessments wurden extrahiert und berichtet. Die Charakteristika der einbezogenen Studien wurden tabellarisch gegenübergestellt. Digitale Therapieprogramme zeigten sich gut akzeptiert und erwiesen sich gegenüber klassischen Formaten als vergleichbar wirksam, mit kontextspezifischen Vorteilen einiger Outcome-Parameter. Digitale Therapien sind – bei gleichzeitiger örtlicher und zeitlicher Flexibilität – ein wirksames Therapieformat.
Chronic conditions are responsible for a growing burden of morbidity, mortality, and cost globally. Despite widespread recognition of the need for preventive care, general practice remains underresourced and primarily focused on treatment. Digital health interventions (DHIs) present a scalable solution to support person-centered preventive care, but evidence regarding the feasibility and acceptability of multirisk consumer-facing interventions in general practice remains limited. This study (ePREVENT-360) aims to evaluate the feasibility, acceptability, sustainability, and preliminary impact on health activation of a consumer-facing DHI, THRIVE (Tailored Health Risk Insights for Vital Empowerment) in Australian general practices. A mixed methods, pre-post feasibility study will be conducted in 5 general practices across New South Wales, Queensland, and Victoria. Adult consumers aged 30 to 65 years will use the THRIVE digital platform to receive chronic condition risk assessments, health scores, and action plans. Quantitative data will include engagement metrics, surveys, and chronic condition risk scores. Qualitative semistructured interviews with consumers and clinicians will provide data about acceptability, engagement, and sustainability. Quantitative data will be analyzed using descriptive and multilevel regression methods, while qualitative data will be analyzed thematically. The study has secured funding in 2024 through an Australian General Practice Research Foundation and Hospital Contribution Fund of Australia Research Foundation Health Services Research Grant. Consumer recruitment commenced in December 2025. Recruitment of the 5 participating general practices was completed in March 2026. As of April 2026, all clinician preintervention interviews have been completed, and consumer recruitment has commenced, with 25 consents obtained. Data collection is ongoing, with follow-up expected to be completed by December 2026. Outcomes will inform the iterative refinement of interventions and future trial designs to assess effectiveness. This study will address a key evidence gap in the digital prevention space by evaluating the feasibility, acceptability, and sustainability of a multicondition DHI embedded in general practices. The findings will support the development of a larger adaptive controlled trial and inform future implementation.
The European Health Data Space (EHDS) regulation introduces a transformative framework for the exchange of health data among EU stakeholders. Among its interoperability measures is the inclusion of the International Classification of Functioning, Disability and Health (ICF) as a standard for documenting functioning in patient summaries and discharge reports. While ICF offers a biopsychosocial lens to complement disease-centric classifications, the availability of interoperable ICF data remains uneven. This structured narrative review examines the readiness of EU stakeholders to exchange and utilize ICF data within EHDS. It explores current practices from the data availability and technical infrastructure perspectives, discusses influencing factors such as legislative frameworks and socio-ethical conditions, identifies gaps, and proposes actionable recommendations for the future. Given the limited data available on this topic, a structured narrative review was performed, including a structured literature search from five databases. Additionally, targeted searches were performed in policy repositories and institutional sources. The search included documents written in English, Finnish, and Italian, and the study objective defined the scope for the literature search. Documents were analyzed to synthesize contextual information across stakeholders, identify gaps, and gain strategic insights. In total, 78 studies and gray literature references are discussed in the synthesis. The available evidence on ICF data infrastructures across EU stakeholders reveals significant disparities. Many countries lack standardized EHR support for structured ICF data storage. There is a need to include and map the ICF to international key terminologies and health informatics frameworks to ensure semantic interoperability. Low professional awareness further hinders data availability. Unequal digital literacy and limited citizen empowerment compromise efficient use of ICF. To address these gaps, a three-phase roadmap is proposed: (1) promoting ICF awareness and structured documentation, (2) advancing technical integration through FHIR and ontology development, and (3) aligning policy and governance to support scaling. Integrating the ICF into EHDS is not merely a technical task; it redefines how health is conceived and measured. By addressing readiness across data, technical, legal, and socio-ethical dimensions, the EU can unlock the full potential of functioning data to improve the well-being of its citizens.
Modern personal technologies, such as smartphone apps with artificial intelligence (AI) capabilities, have a significant potential for helping people make necessary changes in their behavior (e.g., adopt healthier lifestyles). Current research highlights that realizing this potential through the design and use of personal technologies calls for a critical reappraisal of the role of healthcare interventions as the driving force of behavior change and requires a more explicit focus on human agency and experience. This paper contributes to this line of investigation by developing and presenting a conceptual framework, informed by activity theory, which views behavior change as an outcome of the combined agencies of healthcare professionals, technology designers, and, most importantly, the persons themselves. According to the framework, the process of behavior change can be represented as a transformation, achieved through an interplay between the activity systems of intervention, development, and empowerment. In addition to presenting the conceptual framework, we offer insights into how these ideas can be implemented through examples of digital companions. Implications of the analysis for the design of personal technologies for supporting healthier lifestyles, with a special focus on intelligent digital companions, are discussed.
In the current digital era, emotional and mental health challenges are becoming very common. Therefore, it is essential to find new and effective ways to support emotional well-being. In this work, we propose ThinkAI helps individuals to better understand and manage their mental health. This platform offers a secure, explainable, and private space where users can express their thoughts and feelings through journaling. ThinkAI then leverages the help of natural language processing (NLP)-based algorithms to analyze these writings to identify emotional patterns. It tracks the changes in the mental well-being of individuals over time. It also offers visual insights that help users see how their emotional states have evolved during that time period, encouraging reflection, and self-awareness. The proposed system also generates alerts in case of adverse situations. ThinkAI comprises two main components: one focused on detecting early signs of depression, and the other on analyzing emotions. The system uses a combination of classical machine learning methods and modern transformer-based models to achieve accurate and reliable results. Both kinds of models were tested. For traditional models, the Support Vector Machine model reported the highest accuracy (0.920) and Receiver Operating Characteristic - Area Under the Curve (ROC-AUC) (0.97) for depression detection, while Naive Bayes had the best recall (0.947). For emotion analysis, Bidirectional Encoder Representations from Transformers (BERT) performed best with an accuracy of 0.945 and an F1-score of 0.9446, closely followed by robustly optimized BERT approach (RoBERTa) and Distilled Robustly Optimized BERT Approach (DistilRoBERTa). Furthermore, to provide a more comprehensive evaluation of the proposed models, we analyzed the training and validation loss across all models up to five epochs, in addition to reporting accuracy. The results highlight how combining classic algorithms with modern transformer-based deep learning models can create powerful tools for understanding emotional and mental health. Thus, ThinkAI offers a promising step toward real-time monitoring of mental health. This work contributes a technically validated and ethically grounded framework. It can be used for real-time monitoring of an individual's mental well-being, digital therapeutics, and large-scale psychological data analysis.
Digital health interventions can be effective at changing behavior, but achieving long-term adherence remains a challenge. One psychological barrier to health behavior change is future discounting, or the tendency to prefer smaller, short-term rewards over larger, long-term rewards. Episodic Future Thinking (EFT) can disrupt future discounting and is a promising technique for improving health behavior, but such interventions have not been co-designed to address end user needs. This study aimed to co-design an app with end users to deliver an EFT intervention aimed at promoting health behavior change in those in the prerisk phase for chronic conditions. Community members participated in up to 2 series of face-to-face co-design workshops. A prototype of the app was reviewed, and insights were gathered to understand (1) the optimal characteristics of the app and (2) the concepts of future discounting and EFT. Themes were generated using inductive thematic analysis. Participants were South Australian adults (n=30) who were predominately affluent women (27/30, 90%) aged 25-44 years (mean 36.37, SD 5.65 years). Feedback generated from the first workshop series resulted in 26 suggestions of which 15 informed iterative app development. Higher-level principles were identified and categorized into 5 overarching themes: concept acceptance, triggers and barriers, personalization, gamification, and user-friendly interface. This study used co-design methodology to develop an app-based EFT intervention. Ongoing engagement with end users and key stakeholders (eg, health care professionals) is needed to ensure that the app meets changing needs. Future work will aim to evaluate its effectiveness in a large-scale clinical trial.
Extreme outdoor temperatures are known barriers to physical activity and may constrain life-space mobility, the geographic footprint of where people live, work, and recreate, and an important indicator of health and independence among older adults. We conducted a pilot study to evaluate the feasibility of a mobile health (mHealth) app designed to objectively capture life-space and to demonstrate its utility through a downstream analysis of ambient temperature and life-space mobility. Using data collected via an iPhone app from 82 participants in an ongoing cohort study (June 2023-January 2024), we used linear mixed-effects models to examine associations between daily average temperature and 3 objective life-space measures: ellipse area, maximum distance traveled, and total distance traveled. Models were stratified by season and adjusted for relative humidity and sociodemographic covariates. The app successfully captured high-resolution longitudinal mobility data over 2 weeks per participant. There was a significant negative nonlinear association between higher daily average temperature and life-space in the summer. With the peak life-space ellipse area observed at 28.8 °C, for every degree Celsius greater than 28.8 °C, we found a statistically significant decrease in ellipse area by 2.97 km2 (95% CI: -5.45, -0.51; p = .02). Findings were similar for the outcomes of maximum and total distances traveled. This study demonstrates that mHealth technology is a feasible tool for assessing life-space mobility in older adults. Higher temperatures are associated with lower life-space metrics, highlighting the potential of app-derived metrics as digital biomarkers for mobility research.
Background: Conventional electrocardiography (ECG) analysis faces a persistent dichotomy: Expert-defined features provide interpretability but are limited in capturing latent high-dimensional patterns, whereas deep learning approaches achieve strong predictive performance but often lack interpretability and require large annotated datasets. A systematic framework that integrates these paradigms remains needed. Methods: We propose ECGomics, a structured and deployable analytical paradigm that deconstructs cardiac electrical signals into 4 interconnected dimensions: Structural, Intensity, Functional, and Comparative. This taxonomy integrates expert-defined morphological metrics with artificial intelligence-derived latent embeddings to generate multidimensional digital biomarkers. Results: We operationalized this framework into a scalable ecosystem consisting of a web-based platform, a mobile solution (https://github.com/PKUDigitalHealth/ECGomics), and application programming interface invocation. Across multiple representative clinical scenarios-including atrial fibrillation detection, recurrence prediction after cryoablation, screening of severe coronary stenosis in apparently normal ECGs, and maternal cardiac monitoring-ECGomics demonstrated robust predictive performance while maintaining interpretability and relatively low data requirements. These results validate the flexibility and effectiveness of the proposed multidimensional framework. Conclusion: ECGomics establishes an omics-level representation system for ECG analysis, bridging conventional feature engineering and deep learning within a unified taxonomy. By providing a deployable digital biomarker ecosystem, this framework advances scalable precision cardiovascular assessment and data-driven health management.
•High overall openness: Most respondents reported moderate to high willingness to use game-based interventions to improve emotion regulation, mental health, and well-being across diverse countries.•Two distinct user profiles identified: Cluster analysis revealed a high willingness group (43%) and a moderate willingness group (57%), highlighting meaningful heterogeneity in receptivity.•Key predictors of high willingness: Younger age (18-25), male gender, frequent gaming, gaming disorder symptoms, and specific emotion regulation difficulties significantly increased likelihood of high willingness.•Factors associated with lower willingness: Higher impulsivity (low perseverance, high sensation seeking) and emotional unawareness or limited use of regulation strategies were linked to reduced openness.•One of the key findings: Participants showed lower willingness to use game-based interventions preventively than reactively. Game-based interventions show promise for mental health, yet limited research has examined individuals' willingness to engage and the factors shaping openness to these approaches. We aimed to (a) assess the extent to which individuals are willing to use game-based interventions to enhance emotional regulation, mental health, and mental well-being; (b) identify distinct participant profiles characterized by varying levels of willingness; and (c) examine socio-demographic, psychological, and game-related factors associated with this willingness. An online survey of 3745 adults aged 18–79 years from 48 countries assessed socio-demographic characteristics, gaming habits, impulsivity, emotional regulation difficulties, gaming disorder symptoms, and anxiety and depression symptoms. Participants reported relatively high willingness to use game-based interventions for improving emotion regulation, improving mental health, and improving mental-wellbeing when feeling down, and more moderate willingness to use such interventions for improving mental wellbeing when feeling good (M = 3.25; 3.35; 3.26 and 2.93 respectively; 1–4 scale, where 1 is described as “Definitely would not” and 4 is “Definitely would”). Cluster analysis revealed two distinct profiles: a “high willingness” group (43%) and a “moderate willingness” group (57%). Logistic regression results indicated that being younger, male, and having higher gaming frequency, gaming disorder symptoms, and some emotional regulation difficulties dimensions significantly predicted membership in the “high willingness” group. In contrast, higher impulsivity and greater emotional unawareness or limited strategy use predicted a lower level of willingness. Most participants were open to digital mental health tools, with willingness shaped by individual traits, highlighting the value of tailored, culturally inclusive interventions for receptive subgroups, especially young adult gamers. One of the key findings of this study is that participants showed lower willingness to use game-based interventions preventively than reactively. This suggests preventive interventions may require distinct motivational mechanisms, with implications for designing strategies that enhance engagement during periods of well-being.
Health information technology tools, including electronic health records, are ubiquitous in healthcare across the United States. Despite the promise and opportunity of these tools, their benefits have been uneven while also having the unintended consequence of imposing substantial administrative and documentation challenges that are often linked to clinician burnout. The adoption of these tools has been shaped by financial incentives, regulatory programs, and sociotechnical demands tied to reimbursement and quality measurement. Patient-facing technologies, including patient portals and remote monitoring, expand access and engagement, but there are disparities in patient use and they often create burden for clinicians. Advances in artificial intelligence, and particularly large language models, now enable automated documentation, ambient capture of clinical encounters, and clinical decision support-offering potential to reduce clinician burden and enhance care delivery. We envision a future of health information technology in which these tools are fully embedded and integrated into the clinical environment such that they streamline clinical work and workflow, optimize decision-making, and improve patient engagement.
Adolescents are among the most frequent smartphone users worldwide. Yet, few studies have examined how smartphone use appears among minority adolescents, including sexual and gender minority (SGM) youth and children of immigrant parents, who often experience unique stressors and heightened mental-health risk. Passive smartphone monitoring provides a promising, low-burden method for continuously and objectively assessing real-world behavior, offering new opportunities to identify dynamic markers of mental health challenges, including suicide risk, in daily life. The present study evaluated the feasibility of a replicable framework for passive smartphone monitoring among adolescents at high risk for suicidal thoughts and behaviors (STB) and explored longitudinal differences in smartphone-derived behavioral features across minority subgroups. Ninety-nine adolescents aged 11-18 with recent STB completed baseline assessments and installed the iFeel app, which collected passive smartphone data for 6 months, including total and social-media screen time and phone-inactivity-based proxy sleep indicators inferred from nighttime phone inactivity. Participants contributed 1500 participant-weeks of data, with an average of 11.9 weeks of valid monitoring, supporting the feasibility and acceptability of this approach. Daily smartphone use time, social-media activity time, and sleep duration were comparable to normative adolescent data. No significant longitudinal differences emerged between SGM and non-SGM adolescents. However, immigrant-origin adolescents displayed shorter but more stable sleep patterns compared to non-immigrant origins, who exhibited longer baseline sleep with steeper declines over time. Findings highlight passive sensing as a feasible, inclusive, and scalable method for examining real-world behavioral processes associated with STB and mental health outcomes among diverse adolescents. This framework offers a scalable approach that future studies can apply to deepen real-time understanding of mental-health challenges and behavioral patterns among diverse adolescents.
To analyze the monitoring of an intervention for expanding testing, isolation, quarantine, and telemonitoring of Covid-19 (TQT-Covid-Strategy) in an administrative health region of a municipality in Northeastern Brazil. This is an evaluative study, whose object of analysis were data produced in the monitoring of a health intervention (TQT-Covid-Strategy), for six months, in 17 health units, namely 12 Family Health Units and five Health Centers. Monitoring matrices created through field reports, workshops with professionals and managers, and permanent education activities were analyzed. Monitoring took place in the three components of the TQT-Covid-Strategy intervention: expansion of accessibility to testing, monitoring of cases and surveillance strategies, and digital platform. The actions in each component were considered adequate (A), partially adequate (P), and inadequate (I) in relation to the activities determined in the action plan and in the protocol of the TQT-Covid-Strategy. The component of the expansion of accessibility to testing was considered adequate, while the monitoring of cases and surveillance strategies presented partially adequate or inadequate results in many units. As for the digital platform component, there was predominantly adequate performance in relation to registration and access to test results and case reporting. However, the use of other surveillance-related resources, such as contact tracing, was inadequate. Boosting the institutionalization of monitoring can be an important instrument for the implementation and improvement of health interventions. The regular presence of enablers and a widely disseminated protocol, in addition to community health agents, enhanced the intervention. However, partially adequate or inadequate results reinforced the importance of qualification of the work process in primary health care regarding surveillance actions and the use of information and communication technologies.