The global nursing shortage crisis presents a significant challenge to healthcare systems. Digital health technologies, such as communication tools, automation systems, monitoring devices, and information platforms have been proposed as one solution to alleviate the issue by optimizing nursing resources. However, a comprehensive overview of the use and potential of these technologies in optimizing nurses' work and resources is still lacking. The aim of this review is to provide an overview of (a) the digital health technologies used in nursing that may have potential to save nursing resources, (b) which indicators are used to measure the effectiveness of these technologies, and (c) which technologies are found to be effective in terms of saving nursing resources. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews in accordance with the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis. The databases PubMed, CINAHL, and Web of Science were searched. Studies were included if they were peer-reviewed, quantitative, addressed nursing professionals, and considered digital health technologies that specifically aimed to save nursing resources. Relevant data were extracted and synthesized narratively, using an emerging framework. A total of 115 studies were included in this review. Digital health technologies fell into four categories: communication, automation, monitoring, and information technologies. All showed potential for saving resources, with monitoring technologies most often reported as having high potential. Indicators used to measure effectiveness focused on temporal, workforce, and workload resources, and related outcomes including quality of care, patient safety, and cost efficiency. Workforce resources were the most frequently optimized, followed by improvements in patient safety and quality of care. While positive effects were predominant, some studies reported adverse and insignificant effects, indicating variability in effectiveness. Digital health technologies offer promising opportunities to alleviate nursing resource shortages, but their potential seem to vary by type. Monitoring technologies showed the most consistent benefits, while communication and information technologies had mixed effects and automation technologies require further research to clarify their potential. Given the wide range of indicators used to measure potential resource savings, defining common, standardized indicators is essential for systematically assessing the impact of digital health technologies on nursing work and resources. This would enable comparability across studies, strengthen evidence-based decision-making and guide implementation strategies.

Digital literacy training within interventions to support older adults with cardiovascular disease in using technologies: a systematic review.

• Inequitable Access : MyHealth adoption favours women, Spanish nationals, and wealthier users, leaving older adults, migrants, and rural residents behind. • Wealth Bias : Digital health use skews toward higher-income groups, disproving assumptions that tech alone ensures equity. • COVID-19 Surge : Pandemic-driven platform growth didn’t reduce disparities—marginalised groups still lagged. • Key Barriers : Digital literacy, language, and rural infrastructure hinder access, requiring systemic solutions. • Call to Action : Policies must prioritise inclusive design, multilingual support, and rural investment to close gaps. The rapid expansion of digital health technologies during and after the COVID-19 pandemic has reshaped how individuals access healthcare services. While these innovations promise greater efficiency and reach, questions remain about their equitable uptake across different population groups. This study investigates the adoption and sustained use of MyHealth, a digital health platform introduced by the Catalan National Health System in 2015 and widely integrated into primary care delivery. Drawing on longitudinal administrative data covering around 80% of the Catalan population (9.46 million individuals) and over 727 million healthcare records from 2015 to 2023, we analyse patterns of digital engagement using survival analysis and microeconometric modelling. Our findings reveal persistent inequalities in both initial adoption and long-term usage. Engagement is higher among women, Spanish nationals, and individuals from higher-income areas. At the same time, older adults, migrants, and rural residents are significantly less likely to adopt or sustain use of the platform. These disparities were particularly pronounced during the pandemic's peak, when digital health use surged. Concentration indices confirm a clear pro-wealth bias in digital health engagement, challenging the assumption that digitalisation automatically enhances equity. Despite the platform’s wide availability and integration into the healthcare system, structural barriers, including digital literacy, cultural and linguistic accessibility, and infrastructure, continue to shape patterns of use. This study presents one of the first comprehensive, large-scale assessments of digital health inequality in Europe. It highlights the need for targeted, evidence-based policies to ensure that digital health transformation supports rather than undermines equity goals in healthcare access and delivery.

Abstract Digital health technologies (DHTs) are revolutionizing medical research, offering unprecedented insights into health monitoring and disease detection through continuous, real-world data collection. Here we characterize the data in one of the largest and most demographically rich DHT datasets as part of the All of Us Research Program. Through a historic device distribution effort, the program reached a broad range of participants nationwide, yielding a DHT dataset with an expanded a large demographic scope. This dataset contains Fitbit data from more than 59,000 participants spanning 14 years with more than 39 million step observations and 31 million sleep observations. Nearly half (46%) of participants with Fitbit data also contributed electronic health records, physical measurements, genomics and survey data. This resource enables researchers to study relationships between digital health metrics and clinical outcomes, advancing DHT methodologies through its large size, broad representation and multi-modal data linkage.

Abstract Background Everyday digital technologies such as social media, gaming, and internet use are deeply integrated into the lives of children, adolescents, and young adults. While these platforms can foster connection, learning, and entertainment, concerns have grown about their potential to influence mental, physical, and social well-being. Research on this topic has expanded rapidly over the past decade, yet much of it remains cross-sectional, limiting insights into long-term outcomes. Longitudinal studies are essential to capture evolving patterns of digital engagement, identify causal relationships, and guide effective policies and interventions that support youth in navigating digital environments. In particular, evidence is needed to distinguish between beneficial and harmful forms of digital engagement, such as social connection versus problematic use, and to understand how these impacts differ across diverse populations and contexts. The COVID-19 pandemic further accelerated young people’s technology use, underscoring the urgency of examining both risks and opportunities. This review, therefore, synthesizes longitudinal research to map trends, identify knowledge gaps, and inform future directions. Objective The study aimed to systematically identify and map longitudinal studies examining associations between everyday digital technology use (eg, social media, gaming, and internet use) and the health and well-being of youth (25 years or younger) and to chart the types of evidence available by technology category, outcomes, and geographical setting in order to highlight key gaps for future research. Methods A systematic search of PubMed, Embase, and PsycArticles (2014‐2024) was conducted and reported in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). Data extraction covered demographics, digital technology categories, and health outcomes. Studies were grouped into 6 key themes: social media use and mental health, digital addiction and behavioral outcomes, physical activity and digital technology, digital health technologies and cognitive development, parental influence and digital technology, and digital well-being and risk behaviors. Results Of the 456 studies identified, 267 were longitudinal studies relevant to our research aims. Internet use (n=201 studies), social media (n=140 studies), and gaming (n=83 studies) dominated the themes. Mental health was the most frequently assessed outcome, with a focus on anxiety and depression. Geographically, 15% (40/267) of studies originated from low- and middle-income countries, with the majority from high-income settings such as the United States (n=76 studies) and Australia (n=15 studies). Nearly half (131/267, 49%) were published post 2020, reflecting heightened interest during the COVID-19 pandemic. Conclusions Longitudinal evidence on everyday digital technology use and youth health is growing but remains concentrated in mental health outcomes and high-income settings, with notable gaps in physical health, educational outcomes, and equity-focused research. These findings highlight the need for more diverse, methodologically robust longitudinal studies to inform context-sensitive policies and interventions that balance the risks and benefits of digital engagement for young people.

ABSTRACT Background Stroke remains a leading cause of long‐term disability worldwide, and rehabilitation is essential for recovery. Although artificial intelligence (AI)‐related technologies have received growing attention in stroke rehabilitation, the knowledge structure and thematic evolution of this interdisciplinary field remain unclear. Objective To conduct a bibliometric analysis of AI‐related research in stroke rehabilitation from 2005 to 2024 and map publication trends, major contributors, thematic clusters, and emerging topics. Methods Relevant publications were retrieved from the Web of Science Core Collection (WoSCC), including SCI‐Expanded and SSCI, on November 30, 2024. Only English‐language articles and review articles published between January 1, 2005, and November 30, 2024 were included. A total of 3436 records were analyzed using CiteSpace 6.4.R1 Basic, GraphPad Prism 10.1.2, and biblioshiny in R. Analyses covered publication trends, collaboration networks, journal distribution, keyword co‐occurrence, clustering, and burst detection. Results Publication output increased markedly over time, with the United States contributing the largest number of publications. The Swiss Federal Institutes of Technology Domain was among the leading institutions, and Rocco Salvatore Calabrò was among the most productive and highly cited authors. Core publication venues included the Journal of NeuroEngineering and Rehabilitation and IEEE Transactions on Neural Systems and Rehabilitation Engineering . The literature mainly focused on virtual reality, upper‐limb rehabilitation, rehabilitation robotics, machine learning, cognitive rehabilitation, and transcranial direct current stimulation. Recent burst terms, including machine learning, artificial intelligence, and deep learning, indicated growing attention to data‐driven rehabilitation approaches. Conclusions AI‐related research in stroke rehabilitation has expanded substantially, with increasing emphasis on adaptive, data‐driven, and technology‐assisted approaches. This study provides a descriptive overview of the field's major trajectories, emerging gaps, and interdisciplinary directions, and may help inform future research and translational exploration.

Passive digital health technologies (DHTs) are increasingly promoted as scalable tools for detecting Alzheimer's disease and related dementias (ADRD) earlier than routine clinic visits. We searched six major databases for English-language studies published between January 2014 and July 2024 that used passively collected, real-world DHT data for ADRD screening or diagnosis. Thirty studies met the criteria. Population sizes were highly skewed (median = 87; range 12-82,829), and most designs were longitudinal (53%) and fully passive (68%). Wrist-worn accelerometers and photoplethysmography sensors dominated, though several studies also used gait, sleep, voice, radar, or posture-tracking devices. A cross-study synthesis showed that those two modalities were primarily applied to memory, attention, and language tasks. Nineteen studies reported median accuracy, sensitivity, specificity, and precision between 80-90%, with F1-score and AUC medians approaching 78%, though relying on in-sample cross-validation rather than external cohorts. Reference standards varied widely, data-quality criteria were seldom reported, and fewer than 5% shared datasets publicly. Classification was the predominant modeling strategy, with regression emerging only in recent years. Overall, passive DHTs show promise as low-burden triage tools for population-level ADRD screening, but routine deployment will require more diverse cohorts, harmonized reporting, multimodal privacy-preserving analytics, and rigorous human-factors evaluation.

Pulmonary fibrosis, encompassing idiopathic pulmonary fibrosis (IPF) and other fibrosing interstitial lung diseases (ILDs) with a progressive phenotype (PPF), represents a group of chronic, life-threatening conditions associated with significant morbidity, mortality, and socioeconomic burden. Despite advances in antifibrotic therapies, traditional disease-centered management alone is insufficient to address the multidimensional needs of affected patients. This comprehensive review advocates for a holistic, patient-centered approach to the management of pulmonary fibrosis, integrating pharmacological interventions with systematic comorbidity assessment, pulmonary rehabilitation, psychosocial support, nutritional optimization, early palliative care, social and community reinforcement, and digital health technologies. We examine the evidence supporting each dimension of holistic care, discuss current barriers to implementation—including healthcare fragmentation, limited multidisciplinary protocols, and scarce resources—and outline future perspectives centered on precision medicine and integrated care models. By shifting from a purely organ-focused paradigm to a comprehensive, multidisciplinary strategy, clinicians can improve not only disease outcomes but also quality of life and overall well-being for patients living with fibrosing ILDs.

As Saudi Arabia aims to enhance the adoption and utilization of mobile health (mHealth) apps in the health care sector, it is vital to identify the potential challenges that may be faced in the process and how to address them. This study aimed to explore patients' and stakeholders' perspectives regarding the privacy, security, and confidentiality of data collected via mHealth apps in Saudi Arabia. A qualitative research design was used by conducting an in-depth interview with 25 participants, comprising health care workers (HCWs), patients, and mHealth app developers. The interview questions focused on awareness of mHealth apps and issues relating to data security, privacy and confidentiality, benefits of mHealth apps, challenges faced, and features that may improve the utilization of such digital health technologies. Thematic analysis was performed using NVivo software (version 12; QSR International). Patients were relatively less informed regarding events associated with data privacy and security than HCWs. Specific factors were identified to influence patient awareness with HCWs, suggesting the need for patient education and collaboration with cybersecurity organizations. Participants posited that advanced security features, user-friendly features, online consultation for emergencies, remote monitoring features, and taking patient needs into account are important facilitators of mHealth apps. Shared experiences mainly revolved around the accessibility to information and reliability of mHealth apps, while the challenges were related to poor usability, technical difficulties, data security, and data breaches. Patient autonomy, remote monitoring, self-care management, medical adherence, and time and cost-saving summed up the perceived benefits of the mHealth app. These findings may assist policymakers in developing strategies to improve Saudi users' and patients' adoption of mHealth apps and address the concerns raised to benefit significantly from these advanced health care modalities.

The digital divide constitutes a growing form of social inequality, influencing access to, use of, and benefit from digital health technologies. Accurate assessment of this phenomenon requires psychometrically sound measurement instruments, especially in health care contexts. This systematic review aimed to identify and evaluate the psychometric properties of instruments developed to measure the digital divide, with a particular focus on their application in health-related settings. A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) guidelines. Literature searches were performed in PubMed, Scopus, Dialnet, and Web of Science for studies published between 2015 and 2025. Inclusion criteria required studies to report a psychometric evaluation of instruments measuring the digital divide. Four studies met the inclusion criteria (ranging from 875 to 1337 participants). The identified scales primarily measured digital skills and capital. All studies reported adequate internal consistency, with Cronbach α coefficients ranging from 0.70 to 0.94. Structural validity was confirmed through factor analysis in all studies. However, data on temporal stability and responsiveness were absent. Existing instruments show potential for assessing digital inequality in health, but further psychometric validation and cultural adaptation are required. Nursing professionals are encouraged to lead efforts in developing and validating context-sensitive instruments to promote digital health equity.

The advancement of digital health technology through telemedicine offers significant opportunities but also raises serious legal challenges , particularly concerning inaccurate anamnesis and misdiagnosis that May cause substantial harm to patients . Existing legal scholarship and regulatory frameworks in Indonesia predominantly focus on individual liability of medical practitioners , while the criminal liability of telemedicine corporations for systemic failures remains conceptually underdeveloped . This gap leaves corporate accountability insufficiently addressed in cases where patient harm arises from platform- based medical services . This study aims to analyze the forms of corporate criminal liability of telemedicine providers in cases of inaccurate anamnesis and misdiagnosis resulting in patient harm and to examine how Islamic criminal law approaches such liability . Using normative legal research with statutory and conceptual approaches , this study analysis relevant regulations , legal doctrines , and principles of Islamic criminal law . The findings indicate that existing regulations assign responsibility for service quality to healthcare facilities but do not explicitly regulate corporate criminal liability for telemedicine providers . This study advances a theoretical argument that misdiagnosis in telemedicine should be reconceptualized as a form of corporate criminal responsibility rather than merely a professional individual negligence . From the perspective of Islamic criminal law , this article offers a conceptual contribution by applying the doctrine of shakhsiyah iʿtibāriyyah to telemedicine corporations , with diyāt and taʿzīr proposed as appropriate accountability mechanisms . Strengthening the regulatory framework to explicitly recognize corporate criminal liability is essential to enhance patient protection and ensure justice in digital health sector.

Digital health technologies have emerged as a transformative force in modern medicine, particularly in the field of cardiovascular care. With the advent of wearable devices, mobile health applications, telemedicine platforms, and AI-driven diagnostics, the potential to significantly enhance patient outcomes and revolutionize the delivery of cardiovascular care is more significant than ever. These technologies provide real-time monitoring, personalized treatment plans, and enhanced patient engagement, all of which are crucial for effectively managing chronic cardiovascular conditions and preventing adverse events. However, despite the promising potential of digital health, integrating these technologies into routine clinical practice has been met with numerous challenges. These include disparities in access to technology, concerns about data privacy and security, the absence of standardized protocols, and the need for interdisciplinary collaboration. Additionally, the long-term implications of widespread digital health adoption, including its impact on healthcare systems, costs, and the overall quality of care, have not been fully explored. This article addresses these gaps by critically examining the barriers to implementing digital health technologies in cardiovascular care, proposing strategies to overcome these challenges, and discussing the potential long-term effects on healthcare systems and patient outcomes. By doing so, it aims to provide a roadmap for successfully integrating digital health into cardiovascular care, ultimately leading to a more predictive, preventive, and personalized healthcare model.

This meta-analysis study was conducted to evaluate the effect of education-based interventions on the development of deep vein thrombosis (DVT) in patients undergoing orthopedic surgery. In this study, the terms "deep vein thrombosis," "orthopedic surgery," and "patient education" were searched in Turkish and English in the relevant literature published in the last 20 years in the Web of Science, PubMed, ScienceDirect, Scopus, and Google Scholar databases. A total of 8021 studies were found as a result of the search. Six studies that met the inclusion criteria were reviewed. In the meta-analysis, the Odds Ratio (OR) was calculated as the effect size, and Cochran's Q test and I² statistic were used for heterogeneity analysis. Publication bias was assessed using funnel plots and Egger regression tests. The meta-analysis found that the risk of developing DVT was significantly lower in groups that received educational interventions compared to control groups (OR ≈ 0.50, 95% CI: 0.37-0.69, p <0.001). Educational interventions have been effective through mechanisms such as encouraging early mobilization, increasing compliance with anticoagulant medication use, and raising awareness about DVT symptoms (p <0.05). In orthopedic surgery patients, education-based interventions applied in conjunction with pharmacological and mechanical methods are effective in preventing DVT. Systematic integration of patient education programs into clinical practice will contribute significantly to improving patient safety and reducing postoperative complications. Future studies should focus on the integration of digital health technologies and the evaluation of long-term effects. The study has been registered with PROSPERO (CRD420251047966).

Physical activity and sleep influence fatigue in myasthenia gravis (MG), and digital health technologies (DHT) enable objective monitoring of these behaviors in daily life. Using this approach, we evaluated whether a lifestyle intervention targeting physical activity or sleep hygiene could reduce fatigue in MG. In this three-arm, randomized controlled trial (DIG-MG; NCT05992025), 72 MG patients completed 6 weeks of baseline monitoring with a DHT ring (OURA), followed by 12 weeks of (i) physical activity guidance, (ii) sleep hygiene education, or (iii) observation, and a 6-week follow-up. The primary outcome was the MG Activities of Daily Living (MG-ADL) score 1 week postintervention. Secondary outcomes included Fatigue Severity Scale (FSS) scores; exploratory outcomes were DHT-derived physical activity and sleep parameters. Baseline MG-ADL scores were similar (median: 5.0). Postintervention medians were 4.0 (physical activity), 3.5 (sleep hygiene), and 3.0 (control), with no significant differences (p = 0.073). Clinically meaningful MG-ADL improvement occurred in six, seven, and six participants, respectively. FSS scores showed no group differences (p = 0.992), with clinically relevant improvement in eight participants in each intervention group and five controls. Participants were more physically active than expected: 64.7% exceeded 600 MET-min/week at baseline. DHT adherence was excellent. REM sleep was lower than expected, while deep sleep was preserved. Self-reported data aligned with DHT measurements. Digital lifestyle interventions were feasible and well-accepted but did not improve MG-ADL or FSS in this unusually active population. However, DHT-based monitoring may support individualized follow-up, and reduced REM sleep warrants further investigation as a fatigue-related factor.

Decentralised clinical trials of investigational medicinal products.

Sleep disturbances are highly prevalent and clinically significant non-motor features of Parkinson's disease (PD). Although in-laboratory polysomnography remains the gold standard, its limited scalability and ecological validity constrain longitudinal and real-world assessment. Recent advances in digital health technologies have introduced a broad spectrum of portable, wearable, and contactless tools for sleep monitoring. In this scoping review, we systematically map the landscape of digital sleep technologies in PD using a tiered framework based on technical maturity and clinical validation (Tier 1-4), and further classify them by signal modality and sleep symptom domain. Through a systematic review of the literature, we identified 19 studies (Tier 2-4) applying digital biomarkers to assess sleep disturbances in PD, including REM sleep behavior disorder, nocturnal immobility, insomnia, circadian rhythm disturbances, excessive daytime sleepiness, and sleep-related respiratory and movement disorders. We additionally contextualize these findings against the rapid expansion of multimodal and AI-driven Tier 3-4 platforms in the general population. Despite this technological progress, a major translational gap persists in PD, characterized by limited disease-specific validation, small cohort sizes, and insufficient multimodal benchmarking. Multimodal systems leveraging machine learning offer a promising direction by enabling more precise characterization of complex and overlapping sleep phenotypes. Emerging contactless systems further expand the potential for continuous, low-burden monitoring, although their clinical validity remains to be established. Future development of digital sleep biomarkers in PD will require prospective validation against established standards and integration of multimodal data to enable scalable, longitudinal phenotyping and clinical trial applications.

Background Digital health–driven rehabilitation systems incorporating Internet of Things (IoT) technologies have attracted increasing attention as a means to support upper limb motor recovery after stroke. However, detailed clinical descriptions of their implementation in routine inpatient rehabilitation remain limited. Case presentation We report the case of a right-handed man in his forties with right-sided upper limb motor impairment following putaminal hemorrhage. The patient underwent rehabilitation using a digital health–driven IoT-based upper limb rehabilitation system starting approximately one month after stroke onset during the convalescent rehabilitation phase. Intervention The intervention was conducted over a two-week period, consisting of 10 sessions (approximately 40 min per session) as part of routine inpatient rehabilitation. The system integrated a portable smart projector, a three-dimensional motion capture sensor, and a communication robot to deliver interactive, task-oriented training. Five activities of daily living–oriented tasks (wiping, unlocking, squeezing, cup transfer, and typing) were implemented, with task difficulty adjusted by the treating occupational therapist according to the patient's performance. Outcomes Upper limb motor function assessed by the Fugl–Meyer Assessment for the Upper Extremity improved from 63 to 66. Real-world arm use assessed by the Motor Activity Log showed an Amount of Use score of 5 both before and after the intervention, suggesting a ceiling effect, while the Quality of Movement score improved slightly from 4.8 to 5. The patient demonstrated high engagement and adherence throughout the intervention, and no adverse events were observed. Conclusion This case report demonstrates the clinical feasibility of integrating a digital health–driven IoT rehabilitation system into routine inpatient stroke rehabilitation. Although generalization is limited by the single-case design, the present case highlights the potential of IoT-based digital health technologies to support task-oriented training and patient engagement in upper limb rehabilitation.

Abstract Introduction Digital health technologies such as mobile apps and wearable devices provide the opportunities of enhancing medication adherence and facilitating lifestyle modification in chronic disease care. However, their impact in Nigeria remains limited due to low adoption rates. Understanding acceptability, the degree to which potential users consider an intervention appropriate based on what they think or feel about the intervention,[1] is crucial to guide implementation and enhance adoption. Aim This study aimed to assess the acceptability of digital health solutions for medication and lifestyle management among adults with chronic illness. Method A cross-sectional study was conducted among 200 adults (≥18 years) with chronic illness attending outpatient clinics of healthcare facilities in Ibadan between May and September 2025. Participants were recruited consecutively, and data was collected using a validated interviewer semi-structured questionnaire. The acceptability and willingness to use digital health were assessed using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework which assess users’ perceptions across five constructs: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC) and Behavioural Intention (BI).[2] BI was used as the outcome variable reflecting willingness to adopt digital health solutions. Data was analysed using SPSS version 23. Descriptive statistics were used to summarise participant characteristics and construct scores. Multiple linear regression was conducted to identify predictors of behavioural intention to use digital health solutions. The statistical significance was set at p &amp;lt; 0.05. Result Hypertension (66%) and diabetes (12%) were the predominant conditions. The overall acceptability was moderate-to-high (mean 3.88 ± 0.84/5). UTAUT construct means were: PE = 3.89 ± 0.87, EE = 3.93 ± 0.82, SI = 4.26 ± 0.83, and FC = 4.11 ± 0.84. Reliability analysis showed acceptable internal consistency for EE, FC, and BI (α = 0.70–0.79), while PE was lower (α = 0.50). Regression analysis (R2 = 0.181) identified EE as the only significant predictor of BI (β = 0.285, p = 0.002), while PE (β = 0.108, p = 0.180), SI (β = 0.076, p = 0.355), and FC (β = 0.048, p = 0.608) were not significant. No significant differences in acceptability were observed by age group, gender, or education level. Key motivators included doctor’s recommendation (53.5%), ease-of-use (32.5%), and perceived health benefits (11.5%), while main barriers were poor power supply (45%), privacy concerns (30%), reliability and accuracy concerns (29%), and affordability (29%). Conclusion Adults with chronic illness in Ibadan demonstrated moderate-to-high acceptability of digital health solutions, with effort expectancy emerging as the key predictor of willingness to adopt. Acceptability was broadly consistent across demographic groups. Recommendations from healthcare providers, easier setup and use, and perceived benefits with health managements are key drivers for acceptability while affordability, poor internet access, and privacy concerns were common barriers. These findings highlight the need for user-friendly designs and supportive infrastructure to strengthen adoption. Collaborations with healthcare providers and addressing structural barriers may improve uptake, relieve pressure on overstretched health facilities, and support better chronic illness management. The limitation of this study is its predominantly quantitative design which may not fully capture the depth of participants’ perceptions.

The rapid development of digital technologies is reshaping oral health research and care delivery. However, the translation of these innovations into routine clinical and public health application remains limited. This special communication, jointly developed by the International Association for Dental Research's Clinical and Translational Science Network and e-Oral Health Network, explores how principles of translational science can be intentionally aligned with e-oral health research to strengthen the impact of digital innovation on oral health outcomes. Drawing on established translational models, this perspective outlines how coordinated bidirectional research approaches can support the progression of digital oral health interventions from early development to sustainable real-world use. Contemporary e-oral health approaches, including virtual care delivery, intelligent decision support systems, mobile and connected technologies, and advanced digital diagnostics, offer new opportunities to enhance disease prevention, clinical decision making, patient engagement, and population-level surveillance. Evidence to date suggests that these approaches can improve diagnostic performance, expand access to care, and support behavior change. Nevertheless, widespread adoption has been hindered by economic, regulatory, ethical, and workforce-related challenges, creating digital inequities. To overcome these barriers, we introduce an integrated translational research framework for e-oral health based on 3 core pillars: 1) technology and capabilities, 2) workforce capacity and training, and 3) real-world patient care, supported by enabling factors including industry and partnerships, policy and governance, and a strong ethics and regulation foundation. By embedding translational research principles into e-oral health development and implementation, this framework seeks to promote methodological rigor, reproducibility, scalability, and equity. Strategic integration of translational science and e-oral health research has the potential to accelerate the uptake of effective digital solutions and contribute to improving oral health outcomes across diverse populations and health systems worldwide.Knowledge Transfer Statement:This special communication, developed by the International Association for Dental Research's Clinical and Translational Science Network and e-Oral Health Network, explores how translational science frameworks can accelerate integration of digital oral health technologies into practice. Translational science provides structured methods to move innovations from development to implementation, while e-oral health encompasses digital technologies such as teledentistry and artificial intelligence for oral health care delivery. Applying translational principles to e-oral health research can enhance rigor and accelerate evidence-based adoption of digital solutions that improve access and outcomes globally.

This review presents a scoping review exploring the characteristics of value-based oral health care (VBOHC) and the potential to transform the delivery of dental services. VBOHC represents a shift from the traditional fee-for-service model, which prioritises service volume, to a system focused on improving patient outcomes, enhancing preventive care, and optimising cost-efficiency. To identify and synthesise the defining characteristics of VBOHC and assess the potential to enhance patient outcomes, cost-efficiency, and care delivery in dental systems. Following methodology per the Joanna Briggs Institute and guidance per PRISMA-ScR reporting (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews), a scoping review was undertaken to include literature discussing VBOHC across various health care settings. Searches were undertaken in 6 relevant databases. Peer-reviewed quantitative and qualitative studies published in English were included and thematically analysed. A total of 50 studies were included after 185 studies were screened. This research identifies several defining characteristics of VBOHC, including prevention and early intervention, patient-centred care, shared decision making, and outcome-based compensation. The scoping review highlights how VBOHC emphasises preventive care to reduce the incidence of severe dental conditions, particularly benefiting vulnerable populations with limited access to regular care. By encouraging proactive engagement with oral health, VBOHC improves long-term patient outcomes while reducing health care costs. Additionally, VBOHC promotes shared decision making, fostering a collaborative relationship between providers and patients, which enhances patient satisfaction and adherence to treatment plans. For providers, the transition to VBOHC requires significant operational and cultural changes, including adopting new workflows focused on outcomes, incorporating digital health technologies, embracing team-based care models, and integrating dental services into broader health care systems. This review concludes that VBOHC is characterised by patient empowerment and a patient-centred whole system approach. However, successful implementation requires addressing the challenges associated with transitioning from the fee-for-service model, particularly through provider support, infrastructure investments, and policy reforms.Knowledge Transfer Statement:The findings of this scoping review can inform policy makers, dental professionals, and health service planners seeking to implement value-based oral health care models. By understanding the core characteristics, this evidence can support more sustainable, equitable, and efficient dental care delivery across a range of health care settings.