Digital interventions have emerged as promising tools to support mental well-being in diabetes. This review aimed to evaluate the effectiveness of digital health interventions in improving mental health outcomes among adults with diabetes, as well as assess the methodological quality of relevant studies and provide a commentary on research gaps and future directions. Medline, Embase, APA PsycINFO, CINAHL Complete, Scopus, and Cochrane Library were searched until August 2024. Studies were included if they involved adults, assessed at least one psychological measure as a primary outcome at 2 or more time points, used a scalable digital health intervention, employed random or quasi-random allocation to at least one experimental group, and were published within the last five years (January 2019 to August 2024). Of 7033 articles screened, 13 met inclusion criteria. Evidence showed the most promise for improvements to self-efficacy and quality of life. Artificial Intelligence based tools showed potential for reducing diabetes distress, while reductions in anxiety were most apparent in interventions using cognitive behavioural therapy. No consistent improvements were found for depression. Digital health interventions show promise for enhancing self-efficacy and health-related quality of life in adults with diabetes. Future research should prioritise psychological theory integration and inclusion of young adults.
The digital transformation of healthcare, driven by electronic health records, together with the IoT-enabled medical devices and AI-driven analytics, has provided the healthcare with more care and innovation but also created unprecedented levels of cybersecurity vulnerabilities in medical informatics ecosystem. Recent incidents, such as ransomware attacks on pharmaceutical companies, breaches at the European Medicines Agency, and the Indian Council of Medical Research, are just a couple of examples of how the incident that was restricted by one jurisdiction can spread to the research, manufacturing, and data networks around the globe. The study gives a comparative overview of cybersecurity regulation across the United States, the European Union, and India, and examines how the three approaches to risk-based, rights-based, and hybrid regulatory models affect the resilience of the system as a whole. The analysis also indicates structural imbalances in breach notification, medical-device regulation and cross-border data management that disrupts global interoperability. The study ends with recommendations on harmonized international standards, secure-by-design, empower breach-response networks, and improved cooperation by WHO, ITU, and GDHP to make the global health cybersecurity resilient. The paper concentrates on the fact that by redefining cybersecurity as a networked socio-technical challenge, there is a need to have collaboratively designed, globally consistent governance policies to protect digital health systems and deliver continuity, trust, and innovation across jurisdictions.
Digital health technologies are increasingly promoted to address sexual and reproductive health (SRH) gaps among forcibly displaced women in transit. Yet little is known about how such tools intersect with trauma, cultural norms, and inequities in humanitarian care. A 6 months multi-sited ethnographic study (2023-2024) was conducted across MENA transit zones representing contrasting political and infrastructural contexts. Purposive sampling identified 14 forcibly displaced women and 32 SRH/GBV providers for semi-structured interviews. Data were analyzed thematically using a hybrid deductive-inductive approach. Digital SRH tools (apps, AI counselling, and online booking) often reproduced offline gaps: fragmentation, impersonality, and cultural dissonance. Barriers included gendered surveillance, poor connectivity, low literacy, and fears of data misuse. While women valued anonymity and cross-border continuity, they described emotional abandonment when technology replaced human contact. Providers reported moral distress and donor-driven digitalization lacking trauma-sensitive preparation. Without participatory, trauma-informed, and culturally grounded design, digitalization risks deepening SRH inequities. Relational, community-driven approaches that embed women's lived experiences are essential to create safe, responsive SRH technologies in humanitarian contexts.
Telehealth has emerged as a transformative force in health care, offering unprecedented convenience, flexibility, and access. However, its benefits remain unevenly distributed, particularly among low-income, rural, older, and non-English-speaking populations. This literature review explores how telehealth's reliance on digital infrastructure, such as broadband access, device ownership, and digital literacy, can create new barriers that risk deepening existing health disparities. Drawing on recent studies, the review highlights how demographic and socioeconomic factors intersect with digital exclusion, limiting equitable engagement with virtual care. To fulfill telehealth's promise as a tool for health equity, systemic efforts must prioritize inclusive design, infrastructure investment, and culturally responsive support. Emergency nurses, as key facilitators of care transitions, play a critical role in identifying digital barriers and ensuring that all patients are equipped to participate in telehealth-based follow-up care.
Early adolescence is key for adopting healthier lifestyles, yet disadvantaged communities often lack resources to support these changes, perpetuating health inequities. Schools play a crucial role in promoting physical activity and healthy eating. eHealth solutions, like online platforms, offer scalable, cost-effective ways to deliver interventions. These platforms can also enhance adolescent engagement and help bridge health resource gaps. The ePro-Schools project aims to co-design and test an eHealth platform to promote healthy habits among adolescents in socially disadvantaged settings. A randomized controlled trial (RCT) will be carried out with the participation of 6 secondary schools (three controls and three intervention), with a sample size estimated at 1000 students of Central Catalonia (Spain). In the intervention schools, focus groups sessions and meetings with stakeholders have been conducted to co-create the ePro-Schools eHealth platform. Students and school staff are pilot testing the platform to assess the platform's usability, functionality, and layout. Finally, the RCT will be conducted, in which the intervention group will have full access to the ePro-Schools platform (an interactive and informative platform), while the control group will only have access to the informative platform with health literacy content on physical activity, nutrition, and healthy habits. In both groups, adolescents will complete validated questionnaires at baseline, post-intervention, and at the six-month follow-up to assess their physical activity and eating habits, including depressive symptoms, quality of life, social isolation, and mental health. Sociodemographic characteristics will also be collected. Implementation, effectiveness, and cost-effectiveness analysis will be performed. The ePro-Schools project introduces a co-designed eHealth platform that integrates physical activity and healthy eating promotion within schools. The intervention aims to enhance adoption, relevance, and sustainability across diverse settings. ePro-Schools project could reduce health inequalities, improve adolescents' physical and mental well-being, and strengthen daily health habits. The model's scalability and embedded implementation planning may support long-term integration into school systems, informing future policies and contributing to educational engagement, reduced disease risk, and broader population health impact. This trial is registered in ClinicalTrials.gov, with the registration number NCT06792461.
Digital behavioral health platforms extend clinical capabilities beyond traditional appointment-based care, but implementation challenges limit their routine use. Although validated suicide risk screening instruments exist and evidence suggests individuals provide honest responses in digital contexts, how behavioral health organizations implement asynchronous screening remains poorly understood. This exploratory study examined implementation experiences from nine behavioral health organizations that adopted digital suicide screening. Nine behavioral health organizations that implemented remote, asynchronous Columbia Suicide Severity Rating Scale (C-SSRS) screening completed post-implementation surveys. Using a mixed-methods approach combining Interpretative Phenomenological Analysis and VADER sentiment analysis, we identified implementation patterns, organizational adaptations, and provider attitudes across diverse service settings. Implementation challenges clustered into operational, technical, clinical, and systemic domains. Operational challenges involved workflow integration, staff training, and protocol development, while technical challenges included EHR integration, digital divide concerns, and alert volume management. Clinical challenges centered on screening quality, therapeutic rapport, and risk factor evaluation, while systemic challenges reflected resource constraints, crisis response protocols, and staff capacity. Provider attitudes evolved from initial anxiety and role uncertainty in early-stages to strong support among advanced-stage organizations, where 48% expressed very supportive and 32% expressed moderately supportive sentiments. Sentiment analysis of alert-workflow responses indicated generally positive attitudes across organizations (mean score = 0.24 on a scale of -1 to 1). Two preliminary frameworks emerged from analysis: the Service Delivery Ecosystem Framework describes context-specific adaptation patterns observed in this sample, and the Implementation Stage Framework characterizes common progression from initial rollout to mature implementation. These findings offer preliminary considerations for organizations planning digital suicide screening integration.
Digital mental health tools-including telehealth, mobile applications, wearable devices, machine learning, and artificial intelligence-are changing the way patients and providers manage mental health care. This review summarizes the current research findings of digital interventions on patient access to care, the factors impacting personalized care, and overall patient engagement. Gaps of knowledge and future considerations are discussed, including careful observation of existing barriers to care. Clinical recommendations are discussed for clinicians who are considering implementing digital mental health tools into practice.
This article presents a review of examples of digital mental health technology (DMHT) for assessing and treating posttraumatic stress disorder (PTSD), including research supporting these innovative solutions. Tools for assessing PTSD are reviewed, including digital administration of self-report measures, ecological momentary assessment methods, personal sensing, electronic medical record and other naturalistic data sources, and emerging digital assessment tools. Next, DMHTs for PTSD treatment are reviewed, including Internet-based interventions, mobile mental health apps, virtual reality therapy, and several emerging digital interventions. DMHT applications for PTSD have demonstrated promise in research and are beginning to be used in clinical practice.
The Internet of Things (IoT) allows continuous health monitoring through the interconnection of wearable and medical devices with computing and storage infrastructures. As cyber threats grow and the sensitivity of healthcare information increases, data integrity, privacy, and access control become critical concerns in digital healthcare environments. This paper proposes a secure IoT-based healthcare framework that integrates machine learning and blockchain techniques for data protection and intelligent health risk assessment.The proposed framework uses cryptographic hashing, Merkle tree construction, digital signatures, and a threshold-based blockchain validation mechanism to enhance the integrity and secure handling of healthcare data in a permissioned simulation environment. The blockchain validation mechanism is evaluated through simulated tampering, replay, and high-load scenarios to assess the integrity verification capability of the proposed framework.Various machine learning models are trained and evaluated on medical datasets to predict disease risk, and their performance is measured using accuracy, precision, recall, and F1-score metrics. The framework is implemented in Python and deployed in a scalable cloud-based environment. Experimental results demonstrate that the proposed framework improves healthcare data integrity verification and supports reliable predictive performance for secure digital healthcare applications.
In an increasingly technology-driven healthcare environment, digital literacy and clinical decision-making (CDM) are essential competencies for undergraduate nursing students. This study investigates the relationship between digital literacy and clinical decision-making skills among student nurses. A cross-sectional correlational design was employed, involving a convenience sample of 201 undergraduate nursing students at Taif University, Saudi Arabia. Data were collected on campus between August and September 2025 via a secure Google Forms link distributed through official university channels. Analysis included descriptive statistics, independent t-tests to examine sex differences, and Pearson's correlation and linear regression to evaluate the relationship between variables. The nursing students possessed a high level of digital literacy (M = 51.00, SD = 8.44) and a high level of clinical decision-making ability (M = 171.30, SD = 12.60). Female students (M = 51.78) scored significantly higher in digital literacy than male students (M = 44.97), with t(199) = 3.65, p < 0.001. A statistically significant positive correlation was found between the two variables (r = 0.389, p < 0.001), indicating that higher digital competency is associated with stronger clinical decision-making skills. Digital literacy was a significant predictor, accounting for approximately 15.1% (R2 = 0.151) of the variance in CDM scores. Sex differences were highly significant across both domains. Female students reported significantly higher mean digital literacy scores (51.78, SD = 7.73) compared to their male counterparts (44.97, SD = 7.89; t = -3.87, p < 0.001). Furthermore, a significant disparity was observed in clinical decision-making, where female students scored 172.50 (SD = 12.40) compared to 162.03 (SD = 14.15) for males (t = -3.82, p < 0.001). The findings underscore the critical role of digital literacy in clinical performance. The results suggest a need for targeted educational strategies to bridge sex-based competency gaps within nursing education. This ensures all students are prepared for a digitalized healthcare landscape.
The World Health Organization's Integrated Care for Older People (ICOPE) program is an evidence-based and user-friendly approach that supports healthy aging. Despite its demonstrated value, most healthcare professionals remain unfamiliar with its application in clinical settings. Structured training in the ICOPE approach could significantly enhance its adoption and contribute to promoting healthy aging. This study developed within the framework of the European project JA PreventNCD and aims to describe the protocol of a strategy for the implementation of ICOPE framework in Greece. This protocol describes a prospective longitudinal study integrating both educational and research components. During the Implementation Phase - Theoretical Education, approximately 75 healthcare professionals will be recruited to complete training in the ICOPE approach. In the subsequent Implementation Phase - Practical Training and Research, trained professionals will recruit at least 200 older adults aged ≥ 60 years with a Katz Index ≥ 5. They will conduct ICOPE Step 1 screenings and Step 2 assessments, followed by individualized care planning and referrals. Older adults will be assessed twice annually over a 24-month period. Trainees will serve as field researchers, recording assessment data and uploading it to a specifically developed digital platform that supports standardized data entry, longitudinal monitoring, and pseudonymized data export for analysis. The study is expected to enhance healthcare professionals' competencies in early detection of intrinsic capacity and functional decline and promote consistent use of person-centred assessment frameworks in primary healthcare. Biannual monitoring will generate the first national dataset on intrinsic capacity trajectories among Greek older adults. Findings will inform the feasibility, acceptability, and sustainability of ICOPE in Greece and provide evidence to support future scale-up and policy adoption. This protocol represents the first structured effort to embed the WHO ICOPE model within the Greek healthcare system. By integrating professional training, community-based assessment, and digital documentation, the initiative aims to strengthen person-centred care, prevent dependency, and align national ageing policies with international standards.
Digital phenotyping-the moment-by-moment quantification of human behavior using data from smartphones and wearables-offers new pathways for mental health research and care. This review summarizes current trends, tools, and applications of digital phenotyping, highlighting its growing clinical relevance in early detection, symptom monitoring, and personalized interventions. Although studies increasingly demonstrate its feasibility and clinical utility across conditions such as depression, anxiety, and schizophrenia, challenges persist. These challenges include inconsistent data quality, small and nonrepresentative samples, lack of methodological standardization, and pressing ethical considerations about privacy and transparency.
Depression leads to a significant societal burden worldwide, yet most individuals affected lack adequate care. Digital mental health treatments (DMHTs) offer evidence-based, accessible interventions via websites, text messaging, virtual reality, and mobile apps, among other technologies. Studies demonstrate DMHT effectiveness, often comparable to traditional therapies, with high treatment acceptability and satisfaction. Key challenges include poor engagement, high attrition, and limited integration into routine care. Despite these barriers, innovations such as human support, improved reimbursement practices, patient-treatment matching strategies, and emerging AI-driven tools promise to broaden DMHTs' impact and position these programs as a frontline treatment option for depression globally.
The purpose of this study was to measure the effect of motivational interviewing on both reducing internet addiction and digital game addiction in adolescents. A parallel-group randomised controlled trial was adopted. The study population consisted of ninth-grade (14-15 years of age) high school students in a city in Turkiye. The study was completed by 88 participants (experimental: 44; control: 44). The data were collected using a Personal Information Form, the Young Internet Addiction Test, and the Digital Game Addiction Scale. The experimental group received a preparatory session and five weekly motivational interviewing sessions. Instruments were administered to both groups before (pre-test) and after the intervention (post-test), and at follow-up tests 3 and 6 months after the final session. The data were analysed using the two-way mixed design and the Bonferroni Comparison Test. The mean scores of internet addiction and digital game addiction decreased significantly after the motivational interviewing in the experimental group compared to the control group (p < 0.001) in both the post-test and follow-up tests. The present study concluded that motivational interviewing may be associated with reductions in mitigating symptoms of internet addiction and digital game addiction behaviours among adolescents. Motivational interviewing could be implemented to reduce internet addiction and digital game addiction behaviours. Trial registration: The study was registered on a clinical trial database (NCT06721702). The study started on December 11, 2023 (actual date on which the first participant was enrolled). • Internet addiction and digital game addiction are two increasingly important problems among adolescents. • Digital games and online activities negatively affect adolescents' physical, social, and psychological health. • Motivational interviewing was an effective technique to reduce online gaming and internet addiction. • A motivational interviewing program comprising at least six sessions could be implemented to promote behavioural change in adolescents.
Digital twin technology represents a transformative approach in healthcare, creating virtual replicas of physical entities that enable real-time data integration, predictive modelling, and personalised treatment strategies. In urology, this emerging technology offers unprecedented opportunities to optimise patient care through simulation-based decision-making. This narrative review comprehensively examines current applications of digital twin technology in urology, evaluates its clinical utility across various urological conditions, and identifies key challenges limiting its widespread implementation. A comprehensive search was conducted across PubMed, Web of Science, and Scopus databases for literature published between January 2020 and January 2026. Search terms included digital twin, virtual twin, urology, uro-oncology, prostate cancer, renal surgery, and bladder dysfunction. Studies focusing on the development, validation, and clinical implementation of digital twins in urological practice were included. Digital twin technology demonstrates significant potential in uro-oncology for treatment planning, surgical navigation, and disease progression monitoring. Key applications include patient-specific tumour growth simulation in prostate cancer, three-dimensional anatomical modelling for partial nephrectomy, and bladder function prediction in outlet obstruction. Integration with artificial intelligence enhances predictive accuracy and enables real-time surgical guidance. Digital twin technology represents a paradigm shift towards precision urology, though challenges in data integration, computational requirements, validation, and ethical considerations must be addressed before routine clinical implementation. Future developments should focus on standardisation, regulatory frameworks, and prospective clinical validation studies.
Clinical judgment is a core competency across healthcare professions and is commonly conceptualized through Tanner's model, which incorporates four phases of clinical judgment: noticing, interpreting, responding and reflecting. While Tanner's framework has informed assessment and reflection tools, less attention has been paid to how clinical judgment can be facilitated through pedagogical design in digital and blended learning environments. This article presents the new Digital Clinical Judgment Model (DCJM), a pedagogical model developed to support the teaching and learning of clinical judgment in digital nursing education. The DCJM was developed using an iterative conceptual synthesis of Tanner's Clinical Judgment Model, educational theories of sociocultural learning, scaffolding and deep learning, as well as from empirical insights into digital nursing education obtained during the COVID-19 pandemic. The DCJM integrates Tanner's four phases of clinical judgment within three interrelated layers of support: pedagogical structure, social and emotional support and technological support. This approach outlines design conditions that enable meaningful engagement in clinical judgment across digital, blended and practice-based learning contexts. Clinical judgment should be supported through the design of learning environments rather than an outcome to be assessed. This new approach represents a pedagogical rather than an evaluative perspective. As a conceptually grounded pedagogical model, the DCJM offers educators a theoretically informed and practically applicable framework for designing learning environments that support the development of clinical judgment in contemporary nursing education. Further empirical research is needed to determine its usefulness in practice and its impact on student learning and educational design.
Placental histopathology provides important insights into maternal and fetal health, yet the organ's spatial heterogeneity poses significant challenges for objective and reproducible histological analysis. Systematic assessment of cellular and structural composition across placental slides remains limited by the scale and subjectivity of manual evaluation. Quantitative approaches are therefore needed to characterise placental responses to injury beyond visually apparent lesions. We applied the Histology Analysis Pipeline.PY (HAPPY), a biologically inspired hierarchical deep learning framework for quantitative single-cell-resolution analysis of Haematoxylin and Eosin (H&E) slides, to 130 placental parenchyma slides from 62 singleton full-term live births. The dataset included healthy normal controls and four common placental lesion types: infarction, perivillous fibrin, avascular villi, and intervillous thrombosis. Cell-type and tissue-structure compositions were quantified, and slide-level deviation from a healthy reference was assessed using compositional data analysis. Placental slides with lesions exhibited significant cellular composition differences compared with healthy controls, including increased extravillous trophoblast and leukocyte densities and decreased Hofbauer cell densities. These cellular changes were accompanied by tissue-level alterations, particularly increased fibrin deposition and changes in villous structure. Compositional deviation increased with infarction size but not with other lesion types. Notably, compositional differences were also detected in slides without an apparent lesion from placentas with lesion(s) elsewhere, indicating organ-wide responses extending beyond focal pathology. Quantitative deep phenotyping reveals widespread cellular and structural changes associated with placental lesions, including effects not evident on routine histological assessment. These findings demonstrate the potential of AI-based digital histology to complement conventional placental pathology in research and clinical settings.
Self-management behaviors (SMB) are fundamental to outcomes in lumbar disc herniation (LDH), yet those remain frequently suboptimal. Electronic health literacy (eHL) may support SMB, but the mechanisms are unclear. Guided by the Information-Motivation-Behavioral Skills model, we investigated whether patient activation (PA) mediates the association between eHL and SMB among LDH patients, and whether pain intensity moderates this pathway. In this cross-sectional study, 402 patients with LDH were recruited from a tertiary grade-A hospital in Shanghai, China. This study was conducted from November 2023 to April 2025. Data were collected using a general information questionnaire, the eHealth Literacy Scale, the Patient Activation Measure, the Self-Management Scale for Chronic Patients, and the Numerical Pain Rating Scale. Statistical analyses were performed using independent samples t-tests, one-way analysis of variance, Pearson correlation analysis, multiple linear regression, and the PROCESS macro for SPSS. The average SMB score among LDH patients was 24.58 ± 9.67, with significantly higher scores observed in those under 40 years old, employed, holding a bachelor's degree or higher, urban residents living alone, individuals with lower monthly income, and those with fewer hospitalizations. It showed that eHL was positive correlations with PA and SMB, while pain intensity was negatively correlated with three all. PA partially mediated the relationship between eHL and exercise (indirect effect: β = 0.132, 95% CI [0.035, 0.228]) and doctor-patient communication (β = 0.053, [0.014, 0.093]) dimensions of SMB, but not cognitive symptom management. Critically, Pain intensity negatively moderated the indirect effect of eHL through PA: the mediated pathway was decreased by over 60% at high pain levels compared to low pain. This study provides evidence that PA mediates the association between eHL and SMB in LDH. More importantly, his mediation pathway is progressively attenuated by increasing pain intensity, indicating that pain functions as a barrier to the translation of digital health skills into motivation and behavior. These findings support the development of pain-responsive self-management interventions that dynamically adjust support based on real-time pain levels. Not applicable.
Digital dietary assessment tools are highly beneficial for nutrition research and personalized interventions. This paper describes the development and evaluation of eNutriFFQv2.0, an updated online food frequency questionnaire designed to reflect current diets in the United Kingdom (UK). Updates included modernized food lists based on recent UK population surveys, food composition tables, and food portion photos to improve accuracy and user experience. To assess reproducibility, UK adults completed the FFQ twice, 14 days apart; validity was evaluated against a 3-d weighed food record in a sub-sample. Multiple statistical methods were used. After excluding participants with unfeasible energy intakes, 87 participants completed the reproducibility and 53 the evaluation. The final eNutriFFQv2.0 captured 164 items and estimated intake for 56 nutrients and 6 food groups. Agreement with the WFR was acceptable to good for 25 out of the 29 nutrients analyzed (weighted kappa 0.21-0.77), with ≤10% misclassification into opposite quartiles for most nutrients. Bland-Altman plots showed good agreement for energy (176 kcal/d higher in FFQ1) and macronutrient estimates. Reproducibility was good for 24 out of the 29 nutrients analyzed (weighted kappa 0.58-0.85) with <5% misclassification. Mean bias for estimates of carbohydrate, fat, and protein was small (0.0-0.7). Energy estimates were 209 kcal/d (10.7%) higher in the first compared with the second completion of the FFQ. These findings demonstrate that eNutriFFQv2.0 is a valid and reliable tool for assessing nutrient intake in UK adults, offering a practical, scalable solution for research and public health in the context of digital health and personalized dietary interventions.