Digital health technologies offer a promising approach to strengthening self-management capacity among patients with chronic obstructive pulmonary disease (COPD), yet clinical application is hampered by poor adherence, low sustained engagement, and limited self-management ability. Although previous studies have identified general self-management challenges in COPD, few have systematically investigated patients' preferences for digital tools or translated these insights into actionable design principles. This hinders the user-centred development and effective deployment of digital interventions for this population. This study aimed to explore the self‑management challenges and preferences for mobile health (mHealth) among COPD patients, with the ultimate goal of translating these findings into design principles for a persuasive self‑management application. We conducted in-depth personal interviews with 15 patients with COPD and five healthcare professionals to explore the challenges of self-management and preferences for mHealth. Data were analyzed using thematic analysis. Subsequently, a structured expert consultation was held to translate the findings into key principles for a persuasive self-management application. Five themes regarding barriers to effective self-management were identified: (1) negative emotional experience, (2) poor health literacy, (3) insufficient family support, (4) inadequate professional health care, and (5) economic burden. Patients expressed four key preferences for digital health technologies: (1) simplicity, (2) personalized decision support, (3) self-report, (4) early warning of deterioration. Furthermore, the panel discussion distilled these findings into eight essential key principles: motivation, simplicity, credibility, guidance, personalization, self-report, warning, and continuity. This study provides new insights into user-centered mHealth tools for COPD self-management. We derived core design principles from patients' demands to inform targeted digital interventions. These principles require validation in female, higher-literacy and multi-center samples before wide application. Future work will complete the remaining CeHRes Roadmap stages of design, operationalization and evaluation to refine this framework. What is Already Known about this Topic? Many patients with chronic obstructive pulmonary disease hope to use mobile applications to manage their respiratory conditions and daily health. Properly designed mobile applications can assist patients in better self-care. Nevertheless, there are still very few development standards formulated according to the actual daily needs of patients with COPD, which makes it difficult for developers to create self-management applications that are both user-friendly and clinically effective. What this Paper Adds? We collected feedback from patients with chronic obstructive pulmonary disease and medical staff through one-on-one interviews, and also gathered professional advice from an interdisciplinary expert panel. Based on these inputs, we identified practical approaches to support routine health management and developed eight actionable design guidelines for creating user-friendly mobile health tools. The Implications of this Paper Our results help medical teams better grasp what people with COPD actually want from mobile health self-management tools. Clinicians and app developers can build mobile health apps that match COPD users’ real needs and preferences. This work offers clear practical guidance to create health tools that center on the person living with COPD.
Digital health platforms are intended to democratize healthcare, yet they often encounter the "digital health paradox," where tools primarily benefit those with high digital literacy. In the Principality of Asturias (Spain), the Mi asturSalud portal was implemented to foster patient co-responsibility, but its actual usage patterns and equity determinants remain under-researched. To identify distinct behavioral user profiles and analyze the sociodemographic determinants of portal adoption, as well as the predictors of perceived digital barriers, in a Primary Care setting. A multicenter cross-sectional study was conducted (N=384) across four health districts. Predictors of portal adoption and digital barriers were analyzed using mixed-effects logistic regression models, with the health center as a random effect to account for data nesting. Among active portal users (n=138), hierarchical cluster analysis was performed to identify distinct engagement patterns, utilizing the elbow method for cluster selection and Pearson's chi-square tests for profile comparison. Two distinct user profiles emerged: "Comprehensive clinical users" (72.5%), who autonomously access clinical data, and "Limited administrative users" (27.5%), whose interaction is confined to basic transactional tasks. Mixed-effects models revealed that adoption is primarily driven by individual sociodemographic factors, particularly educational attainment and age, rather than geographic or institutional context (ICC = 0.026). Education proved to be a more potent predictor than household income. Significant barriers to engagement included credential complexity and a lack of functional literacy regarding clinical features, disproportionately affecting users with lower educational attainment. A significant "functional divide" exists, where a segment of the population remains limited to superficial administrative interactions. Digital inequality is a transversal issue rooted in individual capabilities and social support structures. Achieving digital equity requires moving beyond mere technical access toward personalized interventions, with Primary Care nursing serving as a critical mediator for fostering functional health literacy.
Patient safety remains a major concern in hospital-based settings because of adverse events, medication errors, communication failures, delayed recognition of clinical deterioration, and inconsistent adherence to safety protocols. Digital health technologies are increasingly used to support patient safety, but their contribution may depend on integration with standardized protocols and multidisciplinary workflows. This scoping review aimed to map evidence on the integration of digital health technologies and standardized protocols for supporting patient safety in hospital-based settings. This scoping review followed the Arksey and O'Malley framework, further refined by Levac et al, and was guided by PRISMA-ScR. PubMed, Scopus, CINAHL, Web of Science, and IEEE Xplore were searched for English-language studies published from 2006 to June 2025. Eligible studies examined digital health technologies integrated with standardized protocols in hospital-based care and reported patient safety-related outcomes. Data were synthesized using descriptive content analysis and thematic synthesis. Twenty studies were included. Four themes were identified: algorithm-based early warning systems for patient deterioration and sepsis risk; barcode medication administration, electronic medication reconciliation, and clinical decision support systems for medication safety; standardized handoff protocols and digital checklists for clinical communication and workflow adherence; and electronic monitoring systems and digital safety toolkits for hand hygiene and fall prevention. Included studies reported study-specific outcomes related to mortality, length of stay, medication errors, adverse drug events, communication accuracy, protocol adherence, hand hygiene compliance, and fall-related outcomes. Digital health technologies may support patient safety when aligned with standardized protocols and embedded in multidisciplinary workflows. Because no formal critical appraisal or quantitative synthesis was conducted, findings should be interpreted as evidence mapping rather than definitive evidence of effectiveness. Future studies should examine implementation quality, alert fatigue, staff training, workflow integration, sustainability, and transferability across hospital contexts.
To characterize the global research landscape, collaboration patterns, and thematic evolution of artificial intelligence (AI) in cardiac arrest care. We conducted a bibliometric analysis of AI and cardiac arrest research using the Web of Science Core Collection and Scopus. We retrieved records on October 29, 2025, limited to English-language articles and reviews. After deduplication, 1,228 publications were included. CiteSpace, VOSviewer, and bibliometrix (R) assessed publication growth, country/institution contributions, collaboration networks, co-citation structures, and keyword dynamics. We included 1,228 publications (2012-2025) with a compound annual growth rate (CAGR) of 22.05%. The corpus comprised 6,994 authors (mean of 7.46 per paper), and international co-authorship accounted for 13.36% of all documents. Forty-eight countries contributed, with the United States leading (134 publications; 10.9%), followed by South Korea (101) and China (77). Seoul National University was the most productive institution (92), followed by Harvard University (60). Aramendi E. ranked first among authors (21), followed by Park J. (17) and Ong M.E.H. (16). Resuscitation ranked first among journals, with 54 publications and 1,350 citations. Keywords shifted from method-focused topics to more clinical, system- and outcome-focused themes. Burst and clustering analyses emphasized early warning/prediction and neurological outcomes, with recent burst terms including "Cerebral Performance Category (CPC)," "brain injury," and "emergency medical services (EMS)." AI-cardiac arrest research is entering a maturing expansion phase characterized by interdisciplinary linkages and a multipolar collaboration structure. The field is shifting beyond algorithmic performance toward transportable, workflow-aware, and outcome-oriented digital health systems.
The public health systems in Latin America are being transformed and restructured with the help of digital technologies and the use of Data analytics. This transformation is occurring in countries where there is a significant imbalance between the amount and quality of health care services provided, as well as between the institutions that provide these services, particularly in Peru. The increased use of digital health technologies, predictive analytics, and interoperable information systems in Peru provides an opportunity for the improvement of the overall performance of Peru's Public Health System through the use of digital health technologies and predictive analytics and therefore also the ability to allocate resources in a more equitable manner and provide improved epidemiological surveillance. In this review, the author examines the role of data analytics in strengthening Peru's public health systems, as well as the main structural, regulatory, and technology barriers inhibiting data analytics' implementation in Peru's public healthcare systems. A literature review was conducted using readily accessible peer-reviewed articles contained within institutional and governmental publications as well as international health governance documents found in Scopus, PubMed, SciELO, Web of Science, and Google Scholar from 2014 through 2026 for the subject areas of digital health, predictive analytics, interoperability, the use of artificial intelligence, and the ways in which these technologies affect the future of public health governance in Peru and throughout Latin America. The research highlights that analytics are improving how chronic diseases are monitored, how quickly diseases are detected, as well as improving the decision-making abilities of health systems and governments across multiple countries within Latin America. Additional barriers still exist in Peru; these include limited interoperability between healthcare organizations, unevenly distributed technology infrastructure, fragmented governance structures, an inadequate amount of technical resources, and continuing differences in the level of provision of technological resources in urban vs. rural areas. In addition, it was identified through the review that the mere adoption of technology alone will not result in a change; rather, it is essential that there be good institutional coordination for implementing and overseeing regulatory practices, ethical governance of the use of this technology, and development of a strategy for ensuring inclusiveness of implementation. Through its proposed integrated analytical framework, this study expands the public health literature by demonstrating how interoperability (including the impact of governance), predictive analytics and equity dimensions of healthcare systems are related to public health systems in Peru. Also, based on findings from this research, public health systems will need to invest for the long term in improving their infrastructure, creating modern regulatory schemes for digital health, training their workforce in using these tools, and developing policies designed to provide digital inclusion to all members of the community if they want to achieve a sustainable digital transformation.
Digital technologies are central to university students' academic, social, and personal lives, offering opportunities for learning and connection while also introducing challenges such as distraction, emotional strain, and difficulties with self-regulation. Despite increasing interest in digital well-being, there is a lack of comprehensive, psychometrically sound instruments specifically designed to assess digital well-being among university students. This study developed and validated the Digital Well-Being Scale (DWS) for use in higher education. A cross-sectional survey was conducted among 1,533 undergraduate and postgraduate students from a public university in Ghana. Scale development involved literature review, expert evaluation, pilot testing, and psychometric validation. Exploratory factor analysis (EFA) was used to identify the underlying factor structure, followed by confirmatory factor analysis (CFA) to evaluate construct validity. Reliability, convergent validity, discriminant validity, and measurement invariance across gender were also assessed. EFA supported a six-factor solution comprising Task Interference, Digital Safety and Responsible Use, Perceived Control and Satisfaction, Digital Life Balance, Emotional Regulation, and Digital Dependence and Frustration. Following CFA-based refinement, a 41-item scale was retained. The six-factor first-order model demonstrated excellent fit to the data and outperformed a higher-order model. The DWS showed satisfactory internal consistency, convergent validity, and discriminant validity across all dimensions. Measurement invariance analyses supported configural and metric invariance across gender, although scalar invariance was only partially supported. The DWS provides a theoretically grounded and psychometrically robust multidimensional measure of digital well-being among university students. The findings suggest that digital well-being encompasses behavioural, emotional, cognitive, self-regulatory, and responsible dimensions of digital engagement rather than representing a single, unidimensional construct. The scale offers a valuable tool for research, screening, and intervention aimed at understanding and promoting digital well-being and digital mental health in higher education settings.
This study assessed the feasibility and acceptability of a new theory- and evidence-based intervention designed to prevent return to pre-admission smoking behaviours after discharge from a smokefree mental health in-patient setting in the United Kingdom (UK). A multi-centre individually randomised controlled feasibility trial with follow-up at 3 and 4-6 months. Acute adult mental health wards of six National Health Service Mental Health Trusts in England. Thirty-eight (17 intervention, 21 usual care) adults who smoked on or after admission to an acute adult mental health in-patient ward and wished to continue reducing or quitting smoking after discharge, enrolled between February and November 2024. The intervention comprised usual care and a 12-week, theory- and evidence-informed support programme including a bespoke resource kit, personalised behavioural support including phone calls and text messages, and access to a digital smoking cessation app with 24/7 live support. It was delivered by trained mental health workers. The comparator group received usual care as per UK national guidance, typically involving brief behavioural support, offers of nicotine replacement therapy and sometimes electronic cigarettes. Primary outcomes included recruitment and retention, intervention acceptability and feasibility of collecting smoking, mental health and economic data. Success criteria for progression to trial were set a priori at a minimum of 60% of the n = 64 target for both recruitment and retention, i.e. at n = 38. Secondary outcomes included measures of smoking, quitting, reduction of cigarette consumption. Acceptability data were collected through exploratory interviews with participants, mental health staff and interventionists. We recruited n = 38 (60%) participants and retained n = 20 (52.6%) at 3 months, and n = 13 (34.2%) at second follow-up. As such, criteria agreed to determine progression to full trial were marginally met for recruitment and not met for retention. Two intervention participants reported maintaining abstinence. Motivation to quit remained higher in the intervention than the usual care group over time, and use of e-cigarettes was overall common (76.9% n = 10 across groups at 4-6 month follow up). Intervention group participants reported valuing the tailored and personalised behavioural support options but engaged little with tailored digital tools. Health economic data collection was feasible, though refinement is needed for future research. A new intervention delivering smoking cessation support to individuals discharged from smoke-free mental health settings was discontinued because key feasibility criteria were not met, highlighting the need for focused reconsideration of recruitment and retention strategies, intervention design and delivery in mental health in-patient populations. Design implications are discussed, taking into account individual patient-level and systemic challenges.
The digital transformation of public health systems has increased the need for a workforce capable of using data science to inform population health decision-making. However, public health workforce development efforts have not fully integrated data science competencies into training and professional development pathways. This paper presents a competency mapping framework, and a proposed national training agenda designed to operationalize data science skills for the public health workforce. Drawing on and synthesizing existing public health competency frameworks, accreditation standards, and governmental public health workforce task analyses, competencies were mapped to an eight-stage Public Health Data Science Life Cycle. Competency gaps were then identified, and additional competencies were developed to address emerging needs in public health data science practice. The analysis found that existing competencies are concentrated in the middle stages of the Public Health Data Science Life Cycle - particularly data collection and management, data analysis and modeling, and data interpretation and implications - with fewer competencies addressing earlier stages, such as problem framing, and later stages, including communication and life cycle preservation. Key gaps were identified in areas including project feasibility and problem definition, data governance and interoperability, bias and ethical data use, data interpretation and visualization, and the communication and translation of findings to inform policy and community action. Building on these findings, this paper proposes a practical framework to guide the integration of public health data science competencies into workforce training and continuing professional learning. By aligning competencies with the full life cycle of public health data science practice, this approach supports a more comprehensive and applied model for workforce development, with the goal of strengthening data-informed decision-making and improving population health outcomes.
Digital workplace transformation has created new psychological challenges for employees, particularly information anxiety encompassing information overload, fear of missing out (IFoMO), technostress, and digital presenteeism. However, cross-cultural research on these phenomena remains limited. This study examines how information anxiety affects employee mental health across Chinese and Western contexts, testing the mediating role of job stress and moderating effects of job autonomy and organizational support. We conducted a cross-sectional comparative study using large-scale datasets (N = 7,773; China n = 2,936, West n = 4,837) from technology workers. Validated scales measured information anxiety dimensions, job stress, mental health outcomes (anxiety, depression, wellbeing), and work resources. Data were analyzed using hierarchical regression, mediation analysis, moderated regression, and multigroup structural equation modeling with measurement invariance testing. Chinese employees reported significantly higher information anxiety (d = 0.38-0.60) and worse mental health outcomes compared to Western counterparts. Information anxiety explained 19%-26% of mental health variance. Job stress mediated 35%-39% of these relationships. Job autonomy (β = -0.12) and organizational support (β = -0.15) significantly buffered negative effects, with moderation effects present in both cultural groups; organizational support showed stronger buffering in Western samples, while job autonomy effects were numerically larger in the Chinese sample. Multigroup SEM revealed culturally-specific patterns: anxiety-stress relationships were stronger in China, while protective effects of work resources were more pronounced in the West. Information anxiety represents a universal but culturally-moderated occupational health risk. Organizations should implement culturally-adapted interventions: proactive information management and enhanced support in collectivistic cultures, while maintaining autonomy and organizational support in individualistic contexts.
Pakistan is confronting the climate crisis as an immediate and systemic threat to national health security rather than an environmental concern. Recurrent floods between 2022 and 2025 affected more than 26 million people, damaged health infrastructure, disrupted essential services, and placed the country at the top of the Germanwatch Climate Risk Index. These shocks have intensified pre-existing health system fragilities by driving surges in malaria, waterborne infections, malnutrition, antimicrobial resistance, and forced displacement, while constraining routine service delivery. Climate-related migration to peri-urban informal settlements has created new epidemiological vulnerabilities characterized by overcrowding, poor sanitation, and outbreaks such as extensively drug-resistant typhoid. Simultaneously, crop losses and food system disruption have worsened child undernutrition in districts already exceeding emergency thresholds, with women and children disproportionately affected because of structural barriers to maternal, neonatal, and immunization services. Climate variability is also increasing the risk of zoonotic spillover and undermining progress toward Universal Health Coverage. We argue that climate change functions as a threat multiplier for Pakistan's health security and must be systematically integrated into health policy and planning. Key priorities include climate-resilient health infrastructure, strengthened integrated surveillance using digital and geospatial tools, prevention-oriented primary care, and operationalization of a One Health framework. Effective intersectoral governance, provincial implementation, and sustained collaboration with international partners, including the World Health Organization, are essential for building a resilient health system capable of maintaining continuity of care during increasingly frequent climate shocks.
Across the United States, linking electronic health record (EHR) data with public health and other publicly available datasets remains a significant challenge due to the lack of a universal patient ID and limited interoperability. While technology exists to overcome these barriers, silos between primary care, tertiary care, and public health (PH) entities continue. AllianceChicago (AC), a network of Federally Qualified Health Centers (FQHCs), participates in two key initiatives, Multi-State EHR-based Network for Disease Surveillance (MENDS) and CAPriCORN, a Federated Data Network, to connect clinical data for public health surveillance, research, and care continuity. AC is working to bridge these efforts to strengthen integration between healthcare delivery and public health systems. A recent project completed using CAPriCORN related to Youth Suicide Prevention analyzed care utilization patterns linking a primary care cohort of youth (age ≤24) hospitalized for suicide attempt or ideation to tertiary care data. Findings revealed gaps in timely follow-up care, with only 16% receiving a primary care visit and 41% a psychiatric visit within 30 days of discharge. These insights informed the development of solutions to improve referral pathways between social and behavioral services and healthcare for care continuity. Similarly, MENDS, leverages standardized EHR data for chronic disease surveillance. AC contributes de-identified data from 17 FQHCs and collaborates with PH agencies using vetted tools to identify geographic risk hotspots and inform program planning. Emerging use cases demonstrate that improved data linkage and infrastructure can enhance PH surveillance and care coordination, paving the way for more effective health systems.
The digital healthcare environment is rapidly evolving, driven by the Internet of Things (IoT), which offers benefits like early diagnosis, monitoring, and cost reductions. However, this growth heightens the risk of cyberattacks, raising crucial concerns about patient safety, data breaches, and the necessity of trust for technology adoption. This study explores patient acceptance of digital health technologies for chronic disease management. A research framework was developed combining Protection Motivation Theory (PMT) and the Task-Technology Fit (TTF) model. This framework was augmented by incorporating comprehensive user-centric, behavioral, and technological dimensions. Data from 603 participants were analyzed using a hybrid methodology of Structural Equation Modeling (SEM) and Artificial Neural Networks (ANNs). The ANN was deployed to capture complex, non-linear relationships among variables, overcoming the linear limitations of traditional SEM to rank predictor importance with higher accuracy. Findings reveal that while cybersecurity concerns exist, they do not actively deter technology adoption; rather, they are statistically secondary to immediate health benefits and system usability, especially for patients with chronic diseases. Factors including functionality, information accuracy, trust, privacy, and training did not significantly influence IoT adoption, while awareness, perceived vulnerability, perceived severity, innovation, risk, and compliance exerted minor effects. This study advances digital health literature by providing a novel, dual-theoretic framework (PMT-TTF) validated through machine learning, demonstrating that utilitarian health value overrides security anxieties in chronic care contexts. The findings offer practical insights for healthcare providers and developers to prioritize user-centric design alongside robust security protocols.
Healthcare hazardous materials represent an increasing challenge to public health, environmental sustainability, and healthcare resilience owing to the growing complexity of waste streams, emerging contaminants, and evolving regulatory requirements. Although numerous reviews have examined individual aspects of healthcare waste management, an integrated critical evaluation linking hazardous waste classification, risk assessment, treatment technologies, regulatory governance, and circular economy strategies remains lacking. This review addresses this gap by critically synthesizing current evidence on the sources, classification, exposure pathways, human and environmental risks, treatment technologies, regulatory frameworks, and sustainable management strategies for infectious, pharmaceutical, chemical, heavy metal, radioactive, plastic, and electronic healthcare wastes. The synthesis identifies inadequate source segregation, infrastructure deficiencies, inconsistent regulatory implementation, and the rapid emergence of medical plastics, antimicrobial residues, and healthcare electronic waste as the principal barriers to sustainable waste management. Comparative evaluation further demonstrates that effective source segregation, context-specific non-incineration treatment technologies, strengthened regulatory governance, digital waste monitoring, and resource recovery within a circular economy framework can substantially reduce environmental impacts, improve operational efficiency, and enhance resource sustainability. By integrating recent advances, identifying critical knowledge gaps, and proposing strategic priorities for research, policy, and healthcare practice, this review provides a comprehensive framework to support the transition towards safer, resource-efficient, and environmentally sustainable healthcare hazardous materials management.
Warm Wales (WW) is a community-based programme addressing fuel poverty and its broader impact on health and well-being. Interventions combine tailored energy advice, practical support, and education with wellbeing and social prescribing projects to improve health outcomes. Fuel poverty is closely linked to poorer health, making evaluating such programmes using housing and health linked data crucial. To describe the demographic, socioeconomic, health, and housing characteristics of individuals supported by WW and examine the programme's impact on primary care interactions. Methodology: An observational longitudinal cohort study linking WW service data with routinely collected electronic health record and administrative data in the Secure Anonymised Information Linkage (SAIL) Databank. Descriptive statistics summarised the WW supported population. Difference in Differences (DiD) compared primary care interactions rates between cases and Coarsened Exact Matched controls. WW supported 4,083 individuals living across 1,317 properties (January 2021-December 2023). Most WW-supported properties were older (65% built before 1966 vs 60.7% in Welsh housing stock) and socially rented (62.3% vs 19.2% in Welsh housing stock 2021). The cohort mirrored Welsh population sex and ethnicity distributions but was notably younger (aged 18 and under 40.1% vs 25.8%), in the most deprived quintile (40.9% vs 24.0%), and predominantly urban (81.5% vs 73.1%). Health characteristics and DiD results are pending approvals. Warm Wales supports younger individuals living in most deprived areas and older housing. These characteristics are consistent with groups at risk of fuel poverty. DiD analyses are ongoing and will assess the intervention's impact on healthcare utilisation.
Wearable devices are increasingly used to monitor and track health, yet the factors shaping adoption remain incompletely understood. Amid longstanding declines in public trust in the U.S. healthcare system, this study examines how trust in healthcare relates to wearable device use. Data from the 2022 Health Information National Trends Survey (HINTS 6) were analyzed in a sample of 6,118 respondents with complete data on trust, wearable use, and key sociodemographic and psychosocial characteristics. Structural equation modeling (SEM) evaluated relationships among trust, wearable use, and four latent constructs: technological aptitude, health literacy, social media use, and perceived competence. Among respondents, 84.8% reported moderate to high trust in the U.S. healthcare system and 33.2% reported using a wearable device in the prior year. Technological aptitude was the strongest correlate of wearable use (β = .88, p < .001), while perceived competence (β = -.68, p < .001) and social media use (β = -.46, p < .001) were inversely associated. Trust was positively associated with technological aptitude (β = .29, p = .005) and health literacy (β = .36, p < .001), and negatively associated with social media use (β = -.19, p < .001). Trust and wearable use demonstrated a negative association (β = -.14, p = .015). Digital readiness and lower healthcare trust together shape wearable adoption, with implications for how clinicians might leverage self-tracking behaviors to rebuild patient-provider relationships.
The use of digitally fabricated esthetic crowns for restoring primary molars has increased with the development of CAD/CAM systems, three-dimensional (3D) printing, and tooth-colored biomaterials. However, the available evidence remains heterogeneous, and the clinical role of customized digital crowns in comparison with conventional pediatric crowns is still unclear. This systematic review aimed to assess the available in vitro and clinical evidence on esthetic customized crowns fabricated using digital workflows for primary molars. A systematic literature search was conducted in PubMed, Scopus, and Web of Science to identify studies evaluating digitally fabricated esthetic crowns for primary molars. Eligible studies included in vitro investigations, clinical studies, randomized clinical trials, and finite element analyses assessing marginal or internal adaptation, fracture resistance, wear behavior, clinical performance, gingival health, or patient and parent satisfaction. Risk of bias was assessed using RoB 2 for clinical trials and the QUIN tool for in vitro studies. Due to heterogeneity in study designs, materials, comparators, and outcomes, a qualitative synthesis was performed. Twenty-four studies were included, 17 in vitro studies, six clinical studies, and one finite element analysis. Most studies evaluated zirconia, 3D-printed resins, PMMA, CAD/CAM composites, or hybrid ceramics. In vitro findings suggested favorable marginal and internal adaptation for several customized digital crowns and material-dependent fracture resistance. Clinical studies reported acceptable short-term performance, although follow-up was generally limited and outcomes varied across materials. Stainless steel crowns remained a highly predictable comparator, while esthetic digital crowns showed potential advantages in esthetics and customization. Digitally fabricated esthetic crowns for primary molars represent a promising restorative alternative, but current evidence does not demonstrate consistent superiority over stainless steel crowns. Further well-designed clinical trials with longer follow-up and standardized outcomes are needed.
As digital health resources become an important source of asthma-related information, this study explored knowledge, perceptions and experiences of eHealth literacy among caregivers of children with asthma. The study was conducted using semi-structured interviews. All interviews were audio-recorded and transcribed verbatim. Thematic analysis was used to analyze the data with NVivo 15 software. Twelve caregivers of children with asthma participated. Thematic analysis of the interviews revealed three major themes: knowledge and understanding of eHealth literacy; experience using electronic information; general views of information literacy. This study highlights the importance of eHealth literacy among caregivers of children with asthma and provides insights into their needs and experiences regarding online health information. Future efforts should focus on developing reliable digital health resources and tailored educational strategies to support caregivers in asthma-related information management.
Robust national evidence on mental health-related service use is necessary to guide equitable policy interventions. We described referrals to mental health services, mental health-related emergency department attendances and hospital admissions amongst secondary school pupils in England, by social strata. We used linked records from state-funded schools and national health services (ECHILD) in England to create a secondary school cohort of 5,629,719 pupils entering Year 7 from 2012/13 to 2021/22. We measured rates of service use by gender, racial-ethnic group, free school meal (FSM) eligibility, the index of multiple deprivation (IMD) and region of residence. Service contacts were captured in the Mental Health Services Data Set and Hospital Episode Statistics. Pupils were followed up until the first chronological event of: service contact, age 21 years, death or end of study (31st August 2022). We found higher rates of mental health-related service use among females, adolescents who were FSM eligible, in the most deprived IMD groups, living in the North of England and from White Irish Traveller and Mixed Black Caribbean-White racial-ethnic groups. Consistently lower rates were estimated for males, adolescents living in London and Bangladeshi, Indian, Pakistani and Black African racial-ethnic groups. There was consistency in relative rates across services, particularly by FSM eligibility, IMD groups and racial-ethnic group. We present the first national estimates of referrals to mental health services, alongside hospital contacts, within a school cohort. We found stark variation in rates of contacts by social strata, which were broadly consistent across service types.
Digital health technology has the potential to increase access to home-based reablement programmes for people living with dementia (PLwD) or mild cognitive impairment (MCI) to support everyday living. Digital Voice Assistants (DVAs) offer a possible solution to overcome usability issues with traditional technologies due to associated cognitive, motor and visual impairments. This paper describes the co-design of a personalised reablement programme to be delivered via DVA. PLwD or MCI (n = 9), their care partners (n = 9) and health professionals (n = 8) participated in the co-design via online workshops and semi-structured interviews. Phases 1-7 of the IDEAS (Integrate, Design, Assess and Share) framework guided this iterative process to develop a product for future feasibility testing. Consensus on essential functions and features was facilitated using the MoSCoW prioritisation method. Transcripts were analysed using a modified thematic framework to inform the reablement programme. Thematic requirements of a cognitive reablement program to be delivered via DVA included (1) Daily Living (self-care, household and cooking), (2) Activity Participation (leisure activities, home hobbies and ad hoc appointments), (3) Emotional Well-being (social connection and coping strategies) and (4) technical requirements (activation, adaptable content, adherence, auditory processing, awareness and training). The IDEAS framework successfully facilitated meaningful engagement from PLwD or MCI, their care partners, and health professionals to integrate user insights and feedback to co-design a personalised reablement program via DVA for subsequent pilot feasibility testing. PLwD and/or MCI, and their care partners contributed by sharing lived experiences for researchers to gain insights; collaboratively identifying behaviours requiring support; creating ideas for solutions; feeding back on prototypes and prioritising program features and functions. Health professionals fed back improvements on prototypes, identifying potential barriers and solutions to implementation of the program.
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