Significant geographic disparities exist in telehealth utilization between rural and urban populations. Advanced practice registered nurses (APRNs) play an increasingly important role in healthcare delivery, particularly in rural areas. Therefore, it is essential to understand telehealth adoption among APRNs and within their workplaces across these distinct geographic contexts. To examine rural-urban differences in telehealth adoption among APRNs and within their workplaces in the United States. A retrospective cross-sectional study was conducted using data from the 2022 National Sample Survey of Registered Nurses. The study sample comprised all APRNs with active licensure and employed in their primary nursing position within the United States as of December 31, 2021. Two-level mixed-effects logistic regression models were employed to assess the association between telehealth adoption and rural-urban location at both the APRN and workplace levels. Telehealth adoption was highly prevalent among both APRNs and their workplaces. Although rural workplaces had higher observed telehealth adoption, this difference was not statistically significant after accounting for state-level, organizational, and patient-level characteristics, as well as census region. There was also no statistically significant difference in telehealth adoption between rural and urban APRNs. This cross-sectional study found a high prevalence of telehealth adoption among APRNs and within their workplaces, with comparable levels across rural and urban practice settings.
Tumor budding (TB) is an independent prognostic biomarker for colorectal cancer (CRC), yet its clinical adoption is limited by labor-intensive and subjective visual scoring. Computational pathology (CPath) algorithms using deep learning offer potential to improve efficiency and reproducibility. Using an international Delphi study, we established consensus requirements to guide validation and clinical adoption of CPath algorithms, aiming to enhance diagnostic accuracy and patient care. A two-round international Delphi process was conducted, involving international experts, to reach consensus on predefined statements. In round 1, baseline characteristics were collected and participants were asked to rank statements representing the minimal requirements for the implementation of a CPath algorithm for TB assessment. After completion of this round, participants received a personalized feedback report summarizing interim results for items that lacked consensus. In round 2, participants re-evaluated their initial responses to statements without consensus, in the light of anonymized group feedback provided in their personalized report. Fifty-nine pathologists participated in round 1, with a 90% response rate in round 2. Consensus was reached for 21 of 29 (72%) minimal requirements. All reached consensus by agreement. Eight statements (28%) remained without consensus after round 2. Agreement was reached on the technical, organizational, ethical, and legal aspects, although some requirements were not agreed upon. This highlights the importance of evaluations that take specific contexts into account, as well as the need for continuous stakeholder engagement throughout the development and implementation phases.
Clinical decision support (CDS) systems can improve care quality, but their implications for equity remain uncertain. We examined whether provider response to CDS alerts differed by patient race and sex in primary care, and whether differences in alert exposure helped explain any observed variation. We conducted a retrospective study using EHR data from a New York City academic health system, focusing on alert-based CDS during outpatient primary care. Logistic regression was used to estimate the likelihood of alert engagement by patient race and sex, while adjusting for encounter and provider factors. We used a generalized structural equation model to assess mediation by alert type, decomposing direct and indirect effects of demographics on response.Direct effects suggest that providers may respond differently to alerts based on patient identity, consistent with interpersonal bias, in which implicit or explicit attitudes shape clinical behavior, and on the context of the visit. Indirect effects highlight disparities in how alerts are assigned across groups, indicating that algorithmic or systemic bias may be embedded within the technology itself. Estimated mediated pathways suggest that even when providers respond uniformly to alerts, unequal exposure can still produce inequitable outcomes. The findings highlight that the type of CDS triggered plays a significant role in differential CDS responses, with provider- and patient-related factors evident in these differences. These findings underscore the need to evaluate not only provider behavior but also the logic and distribution of CDS tools themselves, as both can contribute to disparities in care delivery. Further research should also focus on looking for the potential health impact of the differential response. Digital tools meant to standardize care can unintentionally contribute to which patients receiving care. We investigate whether providers' use of these tools is related to a patient's identity or influenced by the types of tools provided to them in primary care. Using electronic health record data from a large urban health system, we find that providers' responses to alerts are shaped not only by patient identity but also by the nature of the alert itself. Direct effects suggest that providers may engage differently with CDS based on patient demographics, indicating potential interpersonal bias. Indirect effects reveal that certain patient groups are more or less likely to receive specific types of alerts, indicating embedded algorithmic or systemic bias. These findings underscore the importance of evaluating both provider behavior and the design of CDS tools when assessing equity in digital health. Even when providers respond consistently, unequal exposure to alerts can produce inequitable outcomes. Our results underscore the need for more transparent and equity-aware CDS design and implementation strategies that consider both human and technological sources of bias.
Preventing farmers' exposure to pesticides is a major public health issue. However, research on farmers' practices, particularly in high-income countries, rarely explores the combined role of sociodemographic, occupational and psychosocial factors or considers behaviours beyond the use of personal protective equipment. This study investigated pesticide risk prevention behaviours among French farmers, focusing on agricultural specialisation (ie, the main production on the farm), individual characteristics and key psychosocial determinants. A comprehensive telephone survey conducted among French winegrowers or grower-breeders probed their pesticide knowledge, psychological constructs (attitudes and perceptions, social norms and control) and individual and occupational factors. Associations with three preventive behaviours were studied separately by logistic regression. 162 male farmers were surveyed (median age 50, 74% with high school education), including 99 grower-breeders and 63 winegrowers, with differences in farm size, labour structure and employment status. Preventive measures were not implemented systematically: 59% wore gloves, 65% washed their hands and 45% read hazard information on labels. Agricultural specialisation was a major factor influencing behaviour as well as psychosocial determinants (self-efficacy, perceived barriers and social norms). In contrast, sociodemographic factors and knowledge levels had little effect. The adoption of pesticide risk prevention behaviours remains limited over time, even in high-income countries. Our study demonstrates that (1) behaviours relying on distinct determinants should be analysed separately, (2) agricultural specialisation is a major factor influencing behaviours and (3) psychosocial variables play a predominant role in behaviour adoption. This appraisal is crucial for designing an appropriate intervention targeting French farmers.
Scalable and accurate human motion tracking is expected to modernize the diagnosis and prognosis of gait pathologies, sports performance optimization, and human movement research at large. While recent advances in computer vision are promising, innovation has primarily focused on single-view approaches, which are convenient and could be applied to videos from commodity devices, such as smartphones. However, a range of biomedical applications require higher accuracies. Current multi-view tools either lack sufficient accuracy to justify the added burden of camera calibration or require higher-density multi-camera setups that discourage adoption in out-of-laboratory settings. Here, we present DeepGaitLab, an open-source framework that yields accurate three-dimensional (3D) kinematics while operating flexibly across a range of camera configurations, including only two, and foregoes the time-consuming step of inter-camera calibration. Trained on large synthetic data, DeepGaitLab overcomes the accuracy and generalizability constraints of current tools relying on real data. It outperforms both commercial and open-source alternatives and exhibits monotonic accuracy improvement with additional cameras. Unlike existing systems, its accuracy does not degrade when applied to individuals with mobility limitations. We evaluated DeepGaitLab in 80 individuals, including healthy adults, individuals recovering from anterior cruciate ligament reconstruction, individuals recovering from stroke, and ones with mild cognitive impairment, captured in two distinct environments. In addition to outperforming existing tools and demonstrating utility across three clinically distinct populations, DeepGaitLab offers the optional feature to enhance accuracy via an environment-specific fine-tuning strategy without requiring new labeled data. Together, these advancements establish DeepGaitLab as a practical and scalable platform for real-world deployment, bridging the gap between research-grade biomechanics, emerging artificial intelligence (AI) tools, and clinical impact. All the data, code, and trained models are publicly shared.
 The nasal mucosa is the primary defense mechanism of the upper respiratory tract. Its functionality relies heavily on the intricate balance of mucociliary clearance (MCC), mucosal hydration, epithelial tight junction integrity, and local immunological responses. While the detrimental physiological effects of low humidity and cold temperatures on nasal function are extensively documented in the literature, the physiological and pathological impacts of chronic exposure to high relative humidity (RH) and high temperatures-the defining characteristics of tropical and equatorial climates-remain significantly underrepresented and poorly synthesised. Given that approximately 40% of the global population lives in these climate zones, understanding these mechanisms is of paramount importance to global health. This evidence gap is particularly critical for sub-Saharan Africa, where sinonasal disorders constitute a significant and underappreciated component of the otolaryngological disease burden, yet region-specific clinical guidelines remain largely absent. Compounding this, rapid urbanisation across African and Asian tropical cities is accelerating the adoption of air-conditioning, creating novel patterns of indoor-outdoor micro-climatic exposure that may be fundamentally altering the epidemiology of chronic rhinitis. This systematic review aims to comprehensively evaluate the correlation between high ambient humidity in tropical climates and nasal mucosal function. The primary endpoints include mucociliary clearance times, ciliary beat frequency (CBF), mucus rheology (viscoelasticity), epithelial barrier integrity, and the epidemiological prevalence of specific sinonasal disorders such as tropical allergic rhinitis and non-allergic vasomotor rhinitis. A rigorous systematic literature search was conducted in strict adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search spanned PubMed, Scopus, Web of Science, and the Cochrane Library for peer-reviewed articles published between January 1, 2000, and January 1, 2025. Inclusion criteria mandated studies evaluating human nasal mucosal physiology, MCC time, CBF, and humidity levels exceeding 70%. Risk of bias was assessed using the Newcastle-Ottawa Scale for observational studies and the Cochrane Risk of Bias tool for randomised trials. Out of 1,420 initially identified records, 45 studies met the stringent inclusion criteria for qualitative synthesis. The aggregated data indicate a complex, non-linear, U-shaped relationship between ambient RH and MCC efficiency: optimal MCC occurs between 40% and 60% RH, while chronic exposure to tropical humidity (>70% RH) combined with high ambient temperatures (>28°C) is associated with mucosal engorgement, altered mucus rheology characterised by decreased viscosity and elasticity, and a paradoxical slowing of ciliary beat frequency (CBF). Furthermore, the modern tropical lifestyle involves frequent, abrupt transitions between highly humid outdoor environments and cold, desiccating air-conditioned indoor spaces. This 'micro-climatic shock' may contribute to reactive turbinate hypertrophy, disrupted osmotic gradients, and increased susceptibility to perennial aeroallergens such as house dust mites and fungal spores. High ambient humidity in tropical climates is associated with altered nasal mucosal function, including impaired MCC and changes in mucus rheology. These findings highlight the need for climate-specific approaches to the management of sinonasal disorders. Keywords: Nasal mucosa; humidity; tropical climate; mucociliary clearance; rhinitis; air-conditioning.
The recently proposed consensus frameworks for staging and grading in gerodontology represent an important advance toward multidimensional assessment of oral health in older adults. While staging characterises current oral health status by integrating disease burden, oral function, frailty, and care dependency, grading complements this approach by estimating future vulnerability based on oral, systemic, behavioural, and social determinants. Together, these frameworks provide a more comprehensive foundation for personalised, risk-informed geriatric oral healthcare. This correspondence discusses their complementary roles, highlights alignment with contemporary healthy ageing initiatives including the World Health Organisation's Integrated Care for Older People (ICOPE) framework and considers opportunities for integration into comprehensive geriatric assessment. We further discuss key implementation challenges related to clinical feasibility, interdisciplinary collaboration, and adaptation across diverse healthcare systems, particularly in low- and middle-income countries. Finally, we propose pragmatic implementation strategies, including tiered assessment pathways, to facilitate routine clinical adoption. Successful validation and implementation of these complementary frameworks have the potential to strengthen person-centred care, improve interdisciplinary communication, and advance equitable oral healthcare for ageing populations worldwide.
The limited accessibility, availability, and affordability of fertilizers constitutes a major constraint on crop productivity, alongside poor agronomic practices and weather-related environmental pressures. Maximizing nutrient use efficiency (NUE) through the adoption of appropriate agronomic practices and use of local phosphate rock can play a key role in preventing yield collapse. © 2026 Society of Chemical Industry.
Digital health technologies are increasingly used across oncology services, but the available evidence remains concentrated on patient-facing and clinical applications. Organisational perspectives and the involvement of non-clinical professionals remain poorly represented. This scoping review mapped digital health technologies used in adult oncology care, examined their functions for healthcare professionals (HCPs), and assessed the extent and nature of evidence involving non-clinical professionals (NCPs). A scoping review was conducted to identify studies reporting the use of digital health technologies in adult cancer care. PubMed, Embase, CINAHL, and Web of Science were searched for studies published between 2015 and June 2025, and reference lists were hand-searched. Qualitative, quantitative, mixed-methods, pilot, feasibility, and implementation studies were eligible. Findings were synthesised narratively according to the primary function of each technology and the professional groups involved. Forty-one studies were included. The most frequently reported technologies were electronic patient-reported outcome systems, telehealth and telemonitoring platforms, mobile applications, and decision-support or AI-enabled systems. These technologies were used mainly for symptom monitoring, communication, follow-up, survivorship support, clinical decision support, and care coordination. Reported benefits included earlier symptom detection, improved communication, greater patient reassurance, and more structured clinical workflows. Common barriers included limited digital literacy, declining engagement over time, alert burden, workflow misalignment, poor interoperability, and inadequate technical infrastructure. Only three studies explicitly included non-clinical professionals, indicating that organisational and managerial applications remain substantially under-researched. Interoperability and workflow integration emerged as the most consistently supported implementation priorities. Equity, scalability, sustainability, and economic impact require further evaluation. Because evidence involving non-clinical professionals and AI-enabled implementation remains limited, recommendations concerning organisational adoption, AI governance, and workforce preparation should be treated as priorities for implementation research rather than established policy requirements.
Exergames, which combine physical exercise with interactive gameplay, are increasingly being incorporated into fall prevention programs for older adults. Gamified elements, such as real-time feedback and progress tracking, may enhance motivation, engagement, and adherence. Although several systematic reviews have examined the effects of exergaming on balance and physical function, fewer have focused specifically on clinically meaningful outcomes, such as falls and injurious falls, or on indicators that may influence real-world adoption of exergames. This study aimed to evaluate the effectiveness of exergaming interventions for preventing falls and injurious falls in people aged ≥60 years and to synthesize evidence on implementation-related outcomes, including adherence, acceptability, concerns about falling, quality of life, adverse events, and cost-effectiveness. MEDLINE, Embase, CINAHL Plus, PsycINFO, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from inception to February 2025 for randomized controlled trials evaluating exergaming interventions in older adult populations across all settings. Outcomes included fall rate, number of fallers and injurious falls, and implementation-related secondary outcomes. Risk of bias was assessed using RoB 2.0, and certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Data were synthesized narratively and, where appropriate, pooled using meta-analysis. Nine studies (N=1385) met the inclusion criteria. Comparator-specific analyses suggested that exergaming may reduce fall rates compared with active intervention comparators, although the magnitude and certainty of effect varied, and substantial heterogeneity was present across analyses. Moderate-certainty evidence also suggested that exergames reduced the number of older adults experiencing one or more falls at 12-month follow-up compared with usual care (risk ratio 0.75, 95% CI 0.61-0.92). Evidence for injurious falls, quality of life, concerns about falling, adherence, acceptability, and cost-effectiveness was limited or inconsistent. When pooled across all control groups, exergaming interventions were associated with a lower overall fall rate than comparator interventions (incidence rate ratio 0.53, 95% CI 0.41-0.68), although substantial heterogeneity was present (I²=76%). Low- to moderate-certainty evidence suggests that exergames may reduce fall rates, particularly in comparisons with active intervention control groups, and may reduce the number of fallers compared with usual care. These findings indicate that exergaming may offer a useful adjunct to established fall prevention strategies for older adults, particularly where sustained engagement with conventional exercise is challenging. However, substantial heterogeneity, modest sample sizes, and limited long-term follow-up reduce confidence in these estimates, and more rigorous, large-scale trials are needed before routine implementation can be recommended. This review extends previous exergaming syntheses by focusing on clinically meaningful outcomes, including falls and injurious falls, while also considering implementation-related factors relevant to real-world uptake.
Home phototherapy for psoriasis is non-inferior to office-based care, yet adoption remains limited by implementation barriers, inconsistent patient selection, and underrecognized safety gaps. This narrative review synthesizes recent evidence to address these gaps and provide actionable clinical guidance. PubMed and Embase were searched for studies published between January 1, 2020, and March 1, 2026, yielding 12 included studies. Study types included randomized controlled trials (RCTs), observational studies, cost analyses, implementation reports, and technical device comparisons; findings are interpreted by study design without formal risk-of-bias assessment. The LITE randomized trial demonstrates that home narrowband ultraviolet B (NB-UVB) phototherapy is non-inferior to office-based treatment in patients with plaque and guttate psoriasis, with high satisfaction, improved adherence, and reduced indirect costs. Erythema was the most common adverse event and rarely led to discontinuation; long-term safety data remain limited. Home phototherapy is safe and effective for appropriately selected patients with plaque or guttate psoriasis and represents an underutilized, cost-effective alternative to office-based care. This review identifies three gaps that must be addressed to realize its potential: absence of long-term UV exposure and skin cancer data, equity barriers that may paradoxically limit access for the patients who stand to benefit most, and uncharacterized safety risks of over-the-counter devices. Closing these gaps through prospective safety studies, equity-centered implementation, and regulatory oversight will be essential to establishing home phototherapy as a widely accessible, evidence-based standard of care.
Whole-genome sequencing has substantially advanced the understanding of infection transmission but remains underused in everyday infection prevention and control. The UK pioneered genomic medicine through the 100 000 Genomes Project, tuberculosis surveillance, and foodborne disease programmes; yet, a sustainable framework for routine use of genomic medicine in infection prevention and control has not been realised. In June, 2025, the Genomics to Optimise Infection Prevention (GENOTIPE) Network convened clinicians, academics, public health leaders, and the industry to address this implementation gap. A central challenge is not sequencing capacity alone, but ascertaining when and where genomic information is actionable, and how this information can be delivered in a clinically useful and cost-effective way within operational timeframes. In this Personal View, we outline a national implementation roadmap that emphasises prioritised use-cases, coordinated delivery models, and embedded evaluation of clinical, economic, and system-wide impact. Progress will depend on linking targeted implementation with real-world evidence generation to support sustainable adoption across health-care systems.
This paper studies the macroenvironmental consequences of AI adoption in a balanced annual panel of 30 advanced economies (EU-27, the US, UK and Japan) over 1995-2020. We examine both territorial (production-based) and consumption-based CO2 emissions to account for trade-embedded carbon, and we assess adaptation capacity using the ND-GAIN readiness index. AI is measured using an AI capital stock indicator capturing tangible and intangible AI-related assets. Empirically, we estimate fixed-effects models with Driscoll-Kraay standard errors and strengthen causal interpretation for the emissions outcomes using an IV-2SLS design that instruments domestic AI with geography-filtered patenting shocks from major global innovation hubs. We then use panel local projections to trace the dynamic responses of emissions and climate readiness to unexpected AI-growth shocks. The results show that higher AI stock is associated with lower emissions, and the IV estimates support emissions-reducing effects in medium-run stock specifications. The dynamic evidence is more nuanced: territorial emissions rise after an AI-growth shock, peak around the medium-run horizon, and then ease, while consumption-based emissions decline more persistently. AI shocks are also followed by steady improvements in climate readiness. Together, the findings suggest that AI can support decarbonisation and resilience in advanced economies, but its environmental payoff depends on the deployment path and the energy system that absorbs AI-related demand.
The purpose of this study was to examine the relationship between spirituality and resilience among Native American emerging adults who were adopted or fostered as children-an understudied population at heightened risk for adverse outcomes due to the intersection of poverty, intergenerational trauma, cultural assimilation, and out-of-home care experiences. Utilizing a retrospective survey, data were collected from 405 Native American emerging adults ages 18 to 30 who were either adopted or fostered as children at any point from birth to age 17. Regression analysis revealed a small but statistically significant relationship between spirituality and resilience. Gender differences were also observed, with male respondents scoring significantly higher on resilience than female respondents. These findings support the role of spirituality as a modest protective factor, affirming Indigenous cultural/spiritual inclinations and the humanistic framework of interconnected well-being. Implications include the necessity for social work practitioners to incorporate spirituality-informed, culturally congruent interventions, such as facilitating access to traditional ceremonies and spiritual mentors. This study highlights the importance of reclaiming spiritual connections as part of resilience frameworks for Native American youth and emerging adults navigating the challenges of adoption and foster care.
Chest radiography confirms initial nasogastric tube placement but is impractical for repeated verification during feeding and medication administration. Nasogastric tube placement verification practices on the neuroscience unit delayed feedings and medication administration due to radiograph interpretation and physician order wait times. The aim of this quality improvement project was to assess feasibility, usability, and adoption of gastric aspirate pH testing and tube length measurement for ongoing nasogastric tube placement verification after initial chest radiography confirmation. The Stevens Star Model of Knowledge Transformation guided this project and involved assessing relevance and feasibility of the practice change, developing an action plan, implementing the intervention, and evaluating the results. The quality improvement intervention was to use gastric aspirate pH testing along with distal tube length measurement at the nostril exit site, rather than gastric auscultation, for ongoing nasogastric tube placement verification. With 100% staff compliance with workflow and process measures, the project was feasible and usable. A total of 141 gastric aspirate samples were tested over 6 months. Gastric placement was confirmed (pH ≤5.5) in 131 samples. Ten of the 141 samples had a pH of greater than 5.5, indicating placement not confirmed. Postimplementation surveys indicated that staff nurses accepted the practice change. Gastric aspirate pH testing along with tube length measurement is feasible and effective for ongoing nasogastric tube placement verification in patients with stroke and other neurological conditions. The next step is to incorporate suggested process improvements into the next practice change cycle.
Outpatient hysteroscopy offers a potential solution to improve access to gynecological surgical care; however, its widespread adoption remains limited in Canada. This quality improvement study aims to assess safety and efficiency outcomes of a dedicated high-volume OR-based transitional hysteroscopy program. A retrospective observational study of patients who underwent elective hysteroscopy at a single tertiary care centre in Toronto, Canada, between April 3, 2023 and May 9, 2024 was performed. The pre-implementation group (n = 251) comprised patients who underwent hysteroscopy in the 6 months prior to the introduction of a monthly high-volume OR-based hysteroscopy program. The post-implementation group (n = 70) included those who underwent surgery in the 9 months following the program's introduction. Compared to the pre-implementation group, the post-implementation group demonstrated significant reductions in median total OR time (52 [42 - 65] vs. 36 [31 - 39.75] minutes, P < 0.01), procedure length (19 [14 - 29] vs. 14 [10.25 - 18.75] minutes, P < 0.01), and recovery time (136 [112.5 - 172.5] vs. 114 [99.25 - 137.75] minutes, P < 0.01). Surgical wait times did not differ significantly between groups (95 [50 - 182.5] vs. 92 [54.25 - 124.75] days, P = 0.30). There was no statistically significant difference in complication rates. Implementation of a high-volume, OR-based hysteroscopy program improved procedural efficiency without increasing complication or readmission rates. This model represents a feasible transitional approach for institutions aiming to expand toward a fully outpatient hysteroscopy service while maintaining patient safety and optimizing existing OR resources.
Scientific evidence regarding AKI and acute kidney care has advanced in recent years. However, a knowledge gap remains on the implementation of these evidence-based practices (EBPs) into clinical care. Implementation science (IS) is focused on ensuring that this knowledge is translated in an effective, efficient and sustainable fashion. 1) Define the current status of IS; 2) Define a roadmap for accelerating IS with a focus on patient/care partner advocacy, digital tool application, social determinants of health, and resource-limited settings; and 3) Develop a robust and broad research agenda incorporating IS methodology into the programs. ADQI XXXV was conducted through a modified Delphi process with virtual meetings preceding an in-person meeting. Five workgroups were determined a priori to focus on 1) IS definitions and methods applicable to AKI and acute kidney care; 2) IS literature in AKI and acute kidney care; 3) Innovations in IS to accelerate the adoption, adherence to, and sustainment of EBPs in AKI and acute kidney care; 4) IS methods in resource-limited settings; and 5) Recommendations to identify and evaluate EBPs that are ready for implementation or de-implementation. Prior to the in-person meeting, each workgroup met virtually to review the literature and develop framework questions to address their objectives. During the two-day in person meeting, through iterative discussions, questions and supporting statements were finalized. These questions and statements were agreed upon through voting to achieve consensus, defined as agreement of ≥80%. We report a structured multidisciplinary consensus for defining the role of IS in AKI and acute kidney care. Future programs should address these consensus questions and apply these statements along with IS methodology in the translation of science into clinical practice and the implementation/de-implementation of EBPs in clinical care.
With the rapid advancement of artificial intelligence (AI), increasing numbers of Chinese patients incorporate AI tools into clinical consultations. However, directly introducing AI-generated recommendations into the clinical setting often challenges the authority of physicians and may provoke resistance. Therefore, this study explores how patients strategically integrate AI suggestions into medical consultations to preserve harmonious doctor-patient relationships while benefiting from AI. We conducted in-depth interviews with 60 Chinese stakeholders, including both 35 patients and 25 clinicians, and employed an inductive thematic analysis to code and interpret the data. The findings reveal that patients render AI-generated outputs clinically acceptable through four semantic strategies: provenance reframing, cue selection, modal attenuation, and sequential embedding. In the short term, these tactics sustain physician-patient harmony while enabling the integration of algorithmic knowledge into medical decision making. Over time, however, they give rise to a trust-transfer dynamic in which patients progressively benchmark clinicians against AI's explanatory precision and evidentiary transparency, thereby privileging algorithmic rationales over professional judgment. We propose the adoption of clinician-led, AI-augmented models, the establishment of standardized communication protocols, targeted clinician training, and the implementation of robust validation procedures to ensure that AI effectively complements professional judgment, fosters patient trust, and preserves the integrity of clinical decision-making.
Artificial intelligence (AI) and machine learning (ML) are increasingly being applied to preoperative risk prediction in plastic surgery; however, the methodological quality and clinical readiness of these models are yet to be systematically evaluated. This systematic review assessed the quality, risk of bias, and predictive performance of AI/ML preoperative risk prediction models in plastic surgery using the PROBAST+AI framework. Five databases were searched from inception through October 2025. Ten studies met the inclusion criteria, encompassing autologous breast reconstruction (n = 2), alloplastic breast reconstruction (n = 5), head and neck reconstruction (n = 1), burn surgery (n = 1), and aesthetic surgery (n = 1). Random forest was the most frequently used algorithm (n = 4), followed by neural networks (n = 2), deep forest with RUSBoost (n = 1), support vector machine (n = 1), and logistic regression (n = 1). AUC ranged from 0.66 to 0.82 among the 8 studies reporting discrimination. Critical methodological limitations were identified: only 2 studies (20%) performed external validation, 5 of 7 development studies (71.4%) had events per variable <10 indicating inadequate sample size, and 7 studies (70%) did not report model calibration. Pre-reconciliation inter-rater reliability across 102 paired domain-level ratings yielded a Cohen's kappa of 0.240 and Prevalence-Adjusted Bias-Adjusted Kappa of 0.039, consistent with published benchmarks for PROBAST-based systematic reviews. All discrepancies were resolved via structured consensus. Current AI/ML models for preoperative risk prediction in plastic surgery demonstrate variable performance and substantial methodological limitations that preclude clinical implementation. Multi-institutional prospective validation studies with rigorous methodology are needed before clinical adoption.
The growing need for availability of new vaccines, alongside constrained financial and health system resources, necessitates transparent and evidence-based prioritization. A multi-criteria decision analysis (MCDA) approach was applied by the Tanzania Immunization Technical Advisory Group (TITAG) to prioritize new vaccine introductions for 2026-2030. The World Health Organization's New Vaccine Introduction Prioritization and Sequencing Tool (NVI-PST) was adapted to the Tanzanian context. From thirteen candidate vaccines, seven were shortlisted: hepatitis B birth dose, hepatitis B (adult), malaria, measles-mumps-rubella (MMR), meningococcal (Men5), maternal respiratory syncytial virus (RSV), and typhoid conjugate vaccine (TCV). Thirteen criteria across importance (n = 9) and feasibility (n = 4) domains were applied. Evidence was compiled and vaccines were scored through a structured, participatory process. Hepatitis B birth dose ranked highest (combined score 1.9), followed by hepatitis B (adult) vaccine (3.0). Malaria and maternal RSV vaccines were moderate priorities (4.2), while MMR (4.4), Men5 (4.5), and TCV (5.2) ranked lowest. Key system constraints identified included limited cold chain capacity, financing uncertainties, cost of a vaccine and gaps in local epidemiological and economic data. The application of MCDA through the NVI-PST provided a transparent, systematic, and context-specific framework for prioritizing new vaccine introductions in Tanzania. The findings support phased introduction of hepatitis B vaccines while highlighting the need for strengthened surveillance, sustainable financing, and health system capacity to enable future vaccine adoption. This approach offers a practical model for other resource-constrained settings seeking to optimize immunization decision-making.