The study explored healthcare workers' experiences using the AfyaPro Connected Care app and identified key enablers and barriers to its adoption for diabetes and hypertension care in Ghana. The study applied the Technology Acceptance Model (TAM) to examine how perceptions of usefulness and ease of use of the app influence adoption and to address the gap in evidence on mHealth uptake by frontline providers in low- and middle-income country (LMIC) health systems. A qualitative study was conducted with 20 healthcare workers from two healthcare facilities. Semi-structured interviews, guided by the TAM, explored perceptions of the app's usefulness, ease of use, and behavioral intention. The framework was appropriate for examining individual and contextual drivers of technology adoption in resource-constrained healthcare settings. Interviews were transcribed verbatim and analysed thematically. Participants reported positive experiences with the app, noting reduced administrative burden, workflow integration, stronger patient-provider interaction and improved continuity of follow-up. The app enhanced access to specialist care, supported self-monitoring of blood pressure and glucose, and boosted confidence through its intuitive design and structured training. However, challenges persisted, including unstable power and internet connectivity, increased data entry workload, limited patient access and digital literacy, and restricted roles for junior staff. Participants recommended clearer roles, regular supervision, refresher training, and decision-support tools to improve sustainability and equitable adoption. This study adopts a user-centered and context-sensitive approach based on provider experiences. It shows how mHealth tools can be fitted into Ghana's healthcare system, where challenges like limited infrastructure and digital literacy affect use. Innovation is seen as adapting tools and systems through digital literacy training, decision-support in provider workflows, and blended care models, helping to build a fairer and more sustainable health system. Healthcare workers found the mHealth app feasible and acceptable. The findings highlight the potential of digital tools to improve chronic disease care in resource-limited settings. The study demonstrates how contextual factors in LMIC settings reshape key TAM constructs, with clear implications for mHealth policy, scale-up strategies, and refinement of technology adoption theory.

In this review article, we present the current state of artificial intelligence and advanced technologies in air and water pollution monitoring in the USA. Recent studies in this field show promising outcomes, including the ability to generate more granular data in real-time, using predictive analytics to identify and prevent pollution, and better modeling of complex exposure. Compared to traditional monitoring systems, these next-generation technologies show improvements in timeliness and sensitivity. Despite these promising developments, some gaps and challenges remain, including calibration and standardization, interoperability, regulatory fragmentation, funding limitations, digital divide, and stakeholder trust, which impede their broad and equitable adoption. This article points to some best-practice examples, conducts a structured, evidence-focused narrative review and comparative assessment of the different technologies using quantitative findings from existing meta-analyses and large comparative studies, and discusses barriers to implementation. The article concludes by providing some recommendations for practice and policy. Recommendations from this review are primarily related to the development of consistent technical standards and specifications, workforce and community engagement, participatory governance, and ethical frameworks to address the responsible use of AI and the implications of data bias with the need for accountability and transparency. To fully harness the potential of next-generation monitoring systems in pursuit of environmental justice, public health protection, and informed policymaking will require further research and concerted efforts in policy and investment to address these issues.

Artificial intelligence (AI) is rapidly transforming healthcare worldwide, yet the readiness of physicians and medical students to adopt AI-particularly in low- and middle-income settings-remains insufficiently understood. Examining knowledge, attitudes, and practices (KAP) toward AI is essential for informing educational priorities and implementation strategies. This study aimed assessing AI-related knowledge, attitudes, and practices among Iranian physicians and medical students, examine demographic differences, and identify barriers to AI adoption. A cross-sectional survey was conducted using an online convenience sampling approach across medical universities and clinical settings in Iran between June and August 2024. A validated questionnaire was developed based on a comprehensive literature review of existing KAP surveys related to artificial intelligence and digital health which assessed AI-related knowledge (3 items), attitudes (27 items), and practices (5 items). The reliability of the questionnaire was confirmed using Cronbach's alpha and ICC. Descriptive statistics and multivariable logistic regression were used to examine associations between demographic variables and KAP outcomes. Statistical significance was set at p-value < 0.05. A total of 238 participants completed the survey, including 165 physicians (69.7%) and 72 medical students (30.3%). Overall, 61.3% demonstrated good knowledge, 83.2% had positive attitudes, and 58.4% showed good AI-related practice. Medical students had higher mean knowledge scores than physicians (0.62 (SD = 0.32) vs. 0.58 (SD = 0.35); p = 0.025). Younger participants (18-25years) showed higher mean knowledge than those aged > 65years (0.70 (SD = 0.29) vs. 0.36 (SD = 0.36); p = 0.036). Although attitudes toward AI were uniformly positive (97.4% considered AI essential in medicine), practice levels were lower, particularly among participants aged 50-65years (Mean practice score (SD) = 0.52 (0.21); p < 0.01). In adjusted analyses, age 50-65years was independently associated with lower odds of good practice (AOR = 0.12; 95% CI: 0.04-0.41). Despite strong support for AI integration among Iranian physicians and medical students, gaps remain between positive attitudes and real-world AI use, especially among older clinicians. Structured, practice-oriented AI training and improved institutional infrastructure are needed to facilitate effective and equitable adoption of AI in Iran's healthcare system.

Artificial intelligence in general surgery: a national survey on knowledge, utilization, and future expectations

Phage therapy under multiple abiotic stresses: Systematic review on mechanisms of plant disease control

Tropical forests, despite their critical environmental and socio-economic roles, remain highly vulnerable to deforestation, forest degradation, and climate-related disturbances. There is a growing demand for robust and transparent forest monitoring systems, particularly under REDD+, the Paris Agreement’s Enhanced Transparency Framework (ETF), and emerging climate-finance mechanisms. Conventional approaches based on field inventories and traditional remote sensing are often constrained by limited or uneven field data, persistent cloud cover, complex forest conditions, and limited institutional and technical capacity. This review examines how artificial intelligence (AI) and machine learning (ML) are being integrated into remote sensing–based tropical forest monitoring to address these structural constraints. Using a semi-systematic synthesis of peer-reviewed studies, complemented by operational platforms and grey literature, the review assesses AI/ML approaches, remote sensing datasets, and applications relevant to national and large-scale monitoring. Evidence is synthesized across five analytical dimensions: AI/ML model families and workflows, multi-sensor datasets and training resources, operational monitoring platforms, application domains (including deforestation, degradation, and biomass/carbon estimation), and cross-cutting technical, institutional, and governance barriers. The review finds that AI/ML-enabled remote sensing, particularly those combining optical, radar, and LiDAR time series within cloud-based platforms, has substantially improved the automation, scalability, and speed of tropical forest monitoring. However, effective and equitable adoption remains constrained by limitations in training and validation data, dependence on proprietary platforms and data, uneven technical capacity, and unresolved governance and ethical challenges. Emerging solutions, including open and representative training datasets, platform-agnostic processing infrastructures, long-term capacity building, and inclusive data-governance frameworks, are identified as critical enablers of credible and nationally owned AI/ML-enabled forest-monitoring systems. The review highlights that AI/ML can play a transformative role in supporting climate mitigation, biodiversity conservation, and informed decision-making. This potential, however, depends on transparent data governance arrangements, long-term capacity building, and platform-agnostic infrastructures that support national ownership.

Telemedicine has considerably improved HIV care for poorly served populations by increasing access to vital health services and reducing stigma. However, challenges such as limited digital access and different levels of health literacy persist, undergoing a fair health care provision and requiring targeted interventions to ensure that all individuals can effectively use telematic resources. To evaluate how telemedicine can alter HIV care by increasing access, increasing adherence, and addressing system challenges in terms of equity and technology adoption. Telemedicine improves health results for marginalized groups by increasing access to care. However, barriers such as access to technology, digital literacy and privacy concerns persist. To promote an equitable adoption, strategies must include a community-based training, internet solutions at affordable prices and solid privacy protections, promoting an inclusive environment that gives priority to fair health delivery. HIV care greatly improves accessibility and compliance with telemedicine, because it enables remote consultations and management of the treatment. However, equitably accessing it comes with challenges such as digital disparities and varying degrees of health literacy. Specific interventions have to be addressed with these problems so that all patients get benefit from these improved telemedicine services and have optimal health results. Keywords: Telemedicine, HIV care, accessibility, treatment adherence, digital equity, public health, marginalized populations, patient satisfaction.

Rural, regional, and remote hospitals in Australia face barriers to digital transformation, including limited infrastructure, digital literacy, and workforce capacity. This Commentary outlines a pragmatic strategy to build rural digital readiness through the safe implementation of ambient artificial intelligence (AI) scribes as a low-risk starting point for AI adoption. AI scribes use generative AI to convert clinical conversations into documentation. They offer potential to reduce administrative burden and workforce strain while preparing rural health services for future AI use. Although the Victorian Department of Health has established minimum standards for AI scribe use, rural hospitals face unique challenges including lower AI literacy, workforce pressure, and limited research infrastructure. Insights from ongoing implementation research highlight the value of simulation methods to examine usability, workflow effects, and ethical considerations before deployment. Three key enablers support responsible implementation: (1) clinical simulation for research, (2) harmonisation of evaluation metrics, and (3) shared infrastructure for consent, training, and monitoring. Implementing AI scribes provides a practical pathway for rural hospitals to strengthen capability, reduce administrative burden, and build readiness for more advanced clinical AI, supporting safe and equitable adoption across rural Australia.

Digital care in your pocket: The role of technology in exercise, fitness, prevention, and rehabilitation.

Education as a Tool to Navigate Changing Technology in Radiation Oncology.

Abstract Background/Aims Avacopan is an oral C5a receptor inhibitor that was approved for the treatment of severe active granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) following the pivotal ADVOCATE trial, which demonstrated non-inferiority to glucocorticoid-based regimens and a reduced treatment burden. NICE recommended avacopan for routine commissioning in September 2022. As a first-in-class therapy, uptake in routine clinical practice is expected to vary according to local experience and specialist expertise. Understanding early national prescribing patterns may inform strategies to promote equitable access to advanced vasculitis therapies. Methods Secondary care prescribing data were obtained from OpenPrescribingHospitals.net, covering the period from September 2022 to July 2025. This platform uses data from the Secondary Care Medicines Data (SCMD), which represents pharmacy stock control information from all NHS Trusts in England. Monthly prescription volumes were calculated per patient-months and analysed nationally, regionally, and by integrated care board (ICB). Regional prescribing was standardised per 100,000 population using data from the Office for National Statistics (ONS). Temporal trends and inter-regional variation were explored descriptively. Prescribing by ICB excluded NHS Trusts that were mental health, paediatric, community, or specialist hospitals (e.g. oncology or ophthalmology centres). Associations between prescribing volume and ADVOCATE trial investigator participation were assessed using rank-sum statistical testing. Results Between September 2022 and July 2025, 2.9 million avacopan capsules were prescribed in England, corresponding to approximately 16,000 patient-months of treatment (assuming a 60 mg daily dose). National prescribing increased steadily following NICE approval, peaking in October 2024, when approximately 1,127 patients were treated that month. Four monthly data points for South West England were identified as outliers, with markedly higher values than all other regions and time points (four-fold greater than the interquartile range) and were excluded from regional analyses. London consistently demonstrated the highest prescribing rates per 100,000 population. Marked regional variation was observed: more than half of all avacopan prescriptions originated from the top ten ICBs, with Imperial College Healthcare NHS Trust alone accounting for over 10% of the national total. ICBs with an ADVOCATE trial investigator prescribed significantly higher volumes of avacopan (median 332.5 patient-months [IQR 216.1-567.2] vs. 11.1 patient-months [IQR 0-58.3], p value &amp;lt;0.01), suggesting that clinician familiarity and local research engagement influence adoption. While the overall trend demonstrates increasing utilisation, several large ICBs showed persistently low prescribing throughout the study period, indicating unequal implementation across England. Conclusion Since its introduction, avacopan prescribing in England has risen markedly, reflecting gradual incorporation into specialist vasculitis services. However, substantial regional variation persists, likely influenced by differences in clinician experience, commissioning pathways, and local access to expert centres. Targeted education, dissemination of prescribing guidance, and shared clinical networks may help ensure equitable adoption of novel therapies for ANCA-associated vasculitis across the NHS. Disclosure K. Biddle: None. Y. Lim: None. C. Chan: None. M. Russell: None. K. Bechman: None. A. Mahto: None. J. Galloway: None.

Robotics on the Rise, But Not Everywhere: National Trends in Robotic Approach for Colorectal Cancer Surgery.

Americans are steadily moving away from the nuclear family towards an understanding of family less defined by shared DNA or last names. This is especially prominent in the way children are raised. More children are being born to single or unmarried parents, and a fair number of children are being raised by nonparents. Such nonparental caretaking can manifest as “informal adoption,” where there is no biological or legal parent-child relationship but there is a functional parent-child relationship. Certain areas of the law sometimes struggle to keep up with these changes in the meaning society assigns to “family.” Statutory probate law is no exception. Wills and other testamentary instruments grant wide freedom to gift property to the people testators care about when they die, and sometimes those people are not the testator’s nearest blood relatives. Intestacy law, which governs disposition when there is no testamentary instrument, attempts to approximate the testamentary scheme the decedent would most likely have made. Unfortunately, intestacy statutes usually do not consider the possibility of nontraditional family. So, the law reverts to assuming decedents were closest with, and thus would give their property to, their most immediate biological or legal relatives. When informal adoption is at play though, such an outcome can be contrary to the nonparents’ most likely testamentary disposition. Children raised in nontraditional families deserve a place in probate law, especially those who are “informally adopted.” Nonparents raise these children as their own and, for all practical intents and purposes, fulfill a true parental role. These relationships usually foster close emotional ties, so if the nonparents wrote a will, they would likely leave the child a testamentary gift on par with that of a legal child. Arkansas’s intestacy laws fall short of effectuating this. Many states have recognized inheritance rights that arise from such a relationship, but Arkansas has yet to come up with a real solution. It is far past time that the State provides these children with inheritance rights that, first, legitimize their family relationships, and second, better approximate the likely testamentary schemes of informally adoptive parents. Part II of this Note explains what constitutes informal adoption and some relevant principles of American probate law. Part III analyzes why denial of inheritance for informal adoptees in Arkansas is inconsistent with the Arkansas Inheritance Code’s (“Inheritance Code”) intent to approximate most likely testamentary disposition. Part IV proposes solving this problem with equitable adoption by estoppel, a de facto parentage statute, or a statutory extension of Arkansas’s in loco parentis doctrine to the Inheritance Code. Part V concludes with a challenge to both the Arkansas Judiciary and the General Assembly to finally address this glaring problem in state probate law.

The field of behavioral addictions (BA) research addresses activity domains such as excessive gaming, gambling, and other online behaviors that influence public health policies. A failure to embrace open science practices may lead to concerns about the trustworthiness and reliability of its research outputs. This study explored the current use of open science practices among BA researchers, focusing on the adoption, underlying motivations, concerns, and support needs across seven specific open science practices. We distributed an exploratory survey through professional networks, conferences, and social media and received 83 eligible responses (early career researcher [ECRs]: N = 41). The survey covered six domains: general use, frequency, importance, engagement, concerns, and support needs related to open science practices. Most respondents reported positive attitudes toward open science, with preregistration (75% of total N) and data sharing (65% of total N) as the most commonly used practices. Descriptively, ECRs placed greater importance on these practices than their established counterparts, suggesting a potential generational shift. ECRs primarily reported concerns about insufficient knowledge and fear of errors, while established researchers emphasized workload and a lack of incentives. Both groups highlighted the need for increased time, resources, institutional support, and training. Although our findings are descriptive and limited by self-selection and sample bias, they offer initial insights into how open science is perceived and practised in the field. Sustained progress requires coordinated action from individuals, institutions, and professional societies in terms of knowledge transfer and incentives to ensure inclusive and equitable adoption of open science practices.

This systematic evidence mapping study maps and synthesises a small but growing body of empirical work exploring the crossroads between Generative Artificial Intelligence (GenAI) technologies and digital equity concerns in diverse higher education settings. A comprehensive three-stage search methodology, following systematic identification procedures aligned with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR) standards, accessed and evaluated twelve included publications from 1 January 2023 to 30 January 2025 (including online-first articles available by that date). The review extends longstanding digital divide scholarship by focusing specifically on GenAI-related configurations of access, skills, and outcomes in the post-2022 period. Additional contextualisation was provided through selective analysis of the Trust in AI Report 2025 (University of Melbourne & KPMG), which surveyed public attitudes towards AI across 47 countries and examined how employees and students use and experience AI in work and education settings, and is treated here as sector-relevant background survey evidence rather than as an additional empirical strand of the review. Analysis reveals that whilst GenAI technologies demonstrate substantial educational potential, their implementation presents considerable equity implications that warrant systematic examination. Four key barriers to equitable adoption were identified: limited digital infrastructure and connectivity constraints, insufficient artificial intelligence literacy among stakeholders, economic barriers in terms of cost affordability and access costs, and the absence of inclusive, equity-focused institutional policies. Within the limited corpus, regional disparities were emphasised as being particularly severe, with Global South case studies identifying fundamental infrastructural constraints as primary barriers to effective technology integration. Contextual survey data from the Trust in AI Report also suggest gaps between confidence in GenAI uptake and institutional readiness in many jurisdictions, particularly in emerging economies, although these findings are not specific to the higher education sector. Findings indicate that without targeted interventions to incorporate infrastructure development, comprehensive literacy programs, access provisions, and inclusive policy frameworks, GenAI deployment has the potential to exacerbate rather than alleviate existing educational inequities in the contexts studied. This review identifies the main gaps in current research and makes review-derived recommendations to policymakers, higher education institutions, and practitioners to facilitate more equitable GenAI adoption in higher education environments.

This review explores the revolutionary impact of long axial field-of-view (LAFOV) PET/CT imaging in modern nuclear medicine and molecular imaging. LAFOV PET offers extended axial fields-of-view from 50 cm to 200 cm with unprecedented 3D sensitivity, enabling ultra-fast scans at regular doses or ultra-low dose scans at regular scan times as well as simultaneous whole-body dynamic imaging. We discuss the potential of these specifications in facilitating the clinical translation of multi-parametric whole-body PET imaging for superior quantification, lesion detectability, and treatment response assessments across a diverse range of clinical diagnostic and treatment response assessment applications, in oncology, cardiovascular diseases, inflammatory diseases, neurology as well as for systemic multi-organ assessments and other novel imaging applications. Furthermore, we present LAFOV PET's crucial role for optimizing personalized radionuclide therapy via quantitative precision dosimetry and development of theranostic digital twins. Challenges, such as high acquisition costs, large data volumes, and the need for more extensive validation and wider equitable adoption by enhancing cost-effectiveness through novel detector configurations, innovative data-driven correction methods and Artificial Intelligence are also discussed. Ultimately, LAFOV PET has the potential to redefine precision diagnostics and theranostics in nuclear medicine but its currently limited accessibility should be democratized to disseminate its benefits globally and equitably.

Closer and Wealthier, Not Healthier: Proximity and Socioeconomic Status Drive Ambulatory Surgery Center Selection More Than Comorbidity.

By 2050, the global population is expected to reach approximately 10 billion, leading to a projected 50% increase in food demand relative to 2013 levels. If not adequately anticipated, this growing demand will place significant strain on agri-food systems worldwide, with disproportionate impacts on low- and middle-income countries. Moreover, current projections may underestimate the accelerating effects of climate change, political instability, and civil unrest, which continue to disrupt food production and distribution systems. In this context, technological advancements offer a promising pathway to enhance efficiency, improve transparency, and mitigate risks related to food safety, adulteration, and counterfeiting. Emerging innovations can decouple food production from environmental degradation while strengthening monitoring, verification, and accountability across supply chains. This review examines state-of-the-art technologies developed to support traceability and anti-counterfeiting in agri-food supply chains, considering their application across the full spectrum of stakeholders. To provide a system-level perspective, the review adopts a five-layer socio-technical traceability and anti-counterfeiting framework, comprising identity, sensing, intelligence, integrity, and interaction layers, which is used to map enabling technologies and reinterpret the evolution of traceability systems (TS 1.0-TS 4.0) as a progression of functional capabilities rather than isolated technological upgrades. Using this framework, the review analyzes the advantages and limitations of current solutions and clarifies how traceability and anti-counterfeiting functions emerge through technology integration. It further identifies gaps that hinder large-scale and equitable adoption. Finally, future research directions are outlined to address current technical, economic, and governance challenges and to guide the development of more resilient, trustworthy, and sustainable agri-food traceability systems.

Meaning, purpose, and spirituality (MPS) are central to human experience and closely linked to health behaviors, well-being, and clinical outcomes. Despite strong evidence and growing policy support, MPS remains underutilized in routine care. It is vital to the practice of whole-person lifestyle medicine (WPLM), where sustained behavior change depends on deeply held motivations. To synthesize current evidence and expert consensus from a national MPS summit and translate it into practical guidance for integrating MPS into WPLM clinical practice. We summarize evidence for MPS as a driver of health, review definitions, and propose clinically feasible workflows, interprofessional team roles, and implementation tools (e.g., HOPE Note/PHI, FICA, HOPE, CLEAR). We outline community partnerships, documentation practices, and referral pathways, and address policy and payment environments that enable scalable, equitable adoption. MPS-informed care strengthens therapeutic alliance, resilience, adherence, and patient satisfaction; aligns lifestyle goals with "what matters" to the patient; and fits naturally within team-based, whole-person models. Brief structured or conversational assessments can be embedded in intake, follow-up, and transitions, while documentation and huddles propagate insights across teams. Group medical visits and links to community programs extend continuity and belonging. Payment alignment (e.g., group visits, coaching, value-based models) and fit-for-purpose metrics are pivotal for scale. The six-pillar framework of lifestyle medicine (LM) has not previously included spirituality, but recent revisions now allow for initial integration of MPS and progress toward a more complete WPLM. Integrating MPS is not an optional add-on but a foundational component of quality WPLM practice. Clinicians can begin with small, repeatable steps-brief inquiry, purposeful documentation, warm referrals-while systems pursue policy, payment, and measurement alignment. Priorities include establishing standardized, functionally accurate definitions; incorporating MPS components into clinical LM frameworks; conducting implementation studies across settings and populations; developing acceptable accountability metrics; and evaluating effects on clinician well-being.

Smart farming (SF), the use of advanced technologies such as sensors, the Internet of Things (IoT), artificial intelligence (AI), data analytics, and automation, holds great promise for increasing agricultural sustainability as it enables a reduction of inputs while maintaining yield. A general assumption is that biodiversity will benefit from reduced synthetic inputs. We argue that biodiversity benefits will not come automatically, especially within agricultural fields. Rather, technological developments need to embrace ecological targets during future innovations. Done right, with a new framework that integrates ecological and agronomic objectives in decision-making algorithms, SF could restore biodiversity in agricultural landscapes of the Global North, and preserve it in the Global South, while closing the yield gap. However, making agriculture more biodiversity-friendly through SF requires a more interdisciplinary research by scientists, targeted research funding schemes, incentives for the application of these technologies, and supporting strong national and international policies that drive widespread and equitable adoption.