Archives of Public Health

BackgroundThe COVID-19 pandemic required South African public sector HIV viral load (VL) laboratories to scale up Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing while maintaining essential HIV services. This placed additional pressure on diagnostic services. This dual mandate introduced significant occupational and environmental challenges (OEC) for staff that remain underexplored. ObjectiveThis study aimed to investigate the OEC and effects that staff experienced during the implementation of COVID-19 testing at public sector VL laboratories in South Africa. MethodsA quantitative, cross-sectional study utilised a census approach among technical and support staff. Data were collected via a structured REDCap questionnaire using 5-point Likert scales. Pre- and post-implementation challenges were assessed across four domains: workload, environmental conditions (space, ventilation, waste), communication, and PPE availability. Statistical analyses included the Wilcoxon Signed-Rank and Spearmans correlation tests. ResultsPerceived occupational challenges increased significantly across all domains post-implementation. Staff workload saw the highest rise (mean score 3.02 to 3.53). Adverse health effects were pervasive; 80.2% of staff reported burnout/fatigue, and 76.5% reported increased anxiety/stress. A strong positive correlation was observed between post-COVID-19 challenges and adverse mental and physical health outcomes (rho = 0.449, p < 0.001). Furthermore, 35.8% of staff considered resigning due to increased job demands. ConclusionIntegrating COVID-19 testing exacerbated systemic weaknesses, causing measurable psychological injury and threatening workforce retention. Findings suggest that the diagnostic workforce requires formal crisis surge staffing models and institutionalised mental health support to safeguard personnel and maintain essential services during future health emergencies.

Compassion fatigue is a well-documented hazard among healthcare and veterinary professionals, yet the psychological toll on informal caregivers of feral cat colonies, likely numbering several tens of thousands in Portugal, remains largely unexplored. This cross-sectional study examines internal and external factors associated with the secondary traumatic stress component of compassion fatigue among 172 informal caregivers in Portugal. Secondary traumatic stress refers to work-related secondary exposure to individuals who have experienced extremely stressful or traumatic events. Structured telephone interviews assessed sociodemographics, colony management, compassion satisfaction, resilience, spiritual well-being, and perceived social support. Univariate and multivariable linear regression identified predictors of compassion fatigue. Results indicate that 47% of participants experienced moderate compassion fatigue, and 10% reported high levels. Multivariable analysis revealed that caring for large colonies (more than 25 cats) and being unemployed were significantly associated with higher fatigue. Conversely, older age, higher perceived family support, and the resilience dimension of serenity served as protective factors. Interestingly, finding meaning in life was positively correlated with fatigue, suggesting that caregivers who perceive their role as central to their life purpose may become more emotionally invested, increasing vulnerability to distress when unable to help animals. Official colony registration and formal institutional support did not significantly alleviate fatigue. These findings highlight that institutional support alone is insufficient to mitigate fatigue among informal caregivers, who experience significant distress driven by both practical burdens and profound emotional involvement. The most frequently reported concern among caregivers was the inability to cover the costs of feeding and veterinary care for the cats. Interventions must address both external needs (e.g., support to cover veterinary and feeding expenses for the cats) and internal coping mechanisms. Implementing psychosocial support alongside trap-neuter-return programs may also improve caregiver well-being and foster sustainable urban feral cat management. This underscores a One Health perspective, demonstrating that animal health is closely interconnected with human well-being and environmental health.

BackgroundDengue outbreaks have become a severe threat to Bangladesh as the infections and mortality numbers are skyrocketing in recent years. Favorable environmental and anthropogenic conditions have established the capital of Bangladesh, Dhaka city as the epicenter of dengue outbreak. Studies have showed that climate change induced extreme weather events are exacerbating Aedes mosquito breeding and dengue virus transmission conditions. Methodology/Principal FindingsIn this study, short-term (0-6 weeks) associations of maximum temperature and heatwave days on dengue cases in Dhaka city were examined through Distributed Lag Non-linear Model (DLNM) methodology for weekly measurement of 2016-2024, taking into account relative humidity, cumulative rainfall, seasonality and hospital closure effect. Two separate negative binomial models were constructed. The maximum temperature model rendered an overall inverted U-shaped association, where the maximum temperature range of 31.5-33.2{degrees}C showed a sustained elevated dengue risk, with highest risk estimate at 33.2{degrees}C [relative risk (RR): 1.186, 95% CI: 1.002, 1.403]. Whereas, results of weekly heatwave days showed an overall protective effect (RR<1) for dengue cases. The lowest risk of infection was found at 3 heatwave days per week, with RR 0.275 (95% CI: 0.178, 0.423). Multiple sensitivity analyses were conducted for both models to evaluate their robustness. Lastly, the optimized models were analyzed under three distinct sub-periods, to capture the association of exposure variables with predominant circulating serotypes. Conclusions/SignificanceThe findings of the study aim to support public health policymakers and healthcare authorities in designing and implementing effective vector control interventions under emerging climatic emergencies. Author SummaryDengue disease is one of the most buringing issue in Bangladesh in recent years. This vector-borne disease is inherently influenced by climatic variables, i.e., temperature, rainfall, humidity, etc. Moreover, these relations are complex and non-linearly associated. Due to shift in climatic conditions, the occurance of extreme weather events are becoming frequent, with increased magnitude and longer duration. In this study, the nonlinear and delayed association of dengue infections due to the exposure of extreme temperature events were assessed in climate-change vulnerable Dhaka city. To do this, a statistical method was used, called distributed lag nonlinear methodology (DLNM). The results showed that dengue infections had an inverted U-shaped (parabolic) relationship with maximum temperature, while compared to mean maximum temperature, and a suppressive association with heatwaves relative to days without heatwaves. The findings aim to work as an early warning system, and support to policymakes and healthcare authorities to tackle the dengue surge in the changing climate.

Purpose: The GIG-OSH cohort was established to investigate the impact of digital platform work on occupational safety and health (OSH), working and employment conditions, and health in seven countries in Europe. Participants: The cohort comprises 3,945 digital platform workers from seven European countries. The sample includes both web-based workers (e.g., micro-tasking, freelance design) and on-location workers (e.g., delivery, transport). Participants were recruited using non-probabilistic sampling strategies tailored to national contexts, including social media advertising, recruitment through micro-task platforms, and on-site field outreach. Multidimensional data have been collected through online surveys (implemented via REDCap) covering sociodemographic characteristics, working and employment conditions, psychosocial risks, algorithmic management, and physical and mental health indicators. Findings to date: Participants had a mean age of 32.6 years at baseline (SD 10.4), and the majority are male (58.8%), with a higher concentration of migrants in on-location tasks (62.2%) compared to web-based tasks (48.8%). Regarding educational attainment, 55.4% of the total cohort holds a tertiary degree, reaching 64.4% among web-based workers. Platform work intensity varies significantly: on-location workers averaged 85.4 hours of work in the last month, while web-based workers averaged 47.0 hours. Mean income from platform work as a percentage of the national median was 20.6% (SD 22.2). The mean WHO-5 Well-Being Index score was 58.7 (SD 20.3), which is notably lower than the European general population average (69.4), indicating poorer mental health outcomes among cohort members. Future plans: The GIG-OSH cohort represents the first large-scale, longitudinal study examining occupational safety and health among digital platform workers across multiple European countries. Future waves will prioritize developing precise tools to measure hourly earnings and unpaid waiting time. Future research should aim to include underrepresented subgroups, such as medical and domestic care workers, and explore potential linkage with administrative records to evaluate long-term health trajectories and the impact of new EU labour regulations.

BackgroundOverweight and obesity are causing growing public health, economic and clinical burden, particularly within under-resourced communities. There is an urgent need to develop an in-depth understanding of experiences of weight management, and preferences for support within under-resourced communities, with a view to developing more effective weight management interventions. MethodsFocus groups were run in under-resourced communities using storyboarding; a method to facilitate inclusive communication (n=37). Thematic analysis was applied to textual and visual data, and a realist lens applied to provide in-depth insight into weight management experiences and needs. We believe this is the first study to use this combined methodology to explore weight management experiences and needs. ResultsCombining storyboarding with a realist lens, generated four themes. Living circumstances indicated that mental health, individual needs, and cost of weight management services were key contextual factors. Mechanisms of weight management identified emotional eating and portion control to be central to individual weight management. Yo-yo dieting centred on participants experiences of weight regain after attempting weight loss. Weight management intervention needs indicated psychological support was perceived as severely lacking, and the only route to attain sustained weight management. Offering both in-person and online support for weight management was considered important to reach more people. ConclusionMoving weight management support from short- to long-term and incorporating more robust psychological support would better serve the needs of people living in under-resourced communities who are overweight or obese. Ideally interventions should be multicomponent and tailored to individual needs and circumstances.

Emergency nursing is essential to healthcare systems worldwide. Triage plays a pivotal role in emergency nursing, prioritizing patients based on the urgency of their medical condition and focusing on rapid assessment and prioritization of patient care according to their condition and its severity. In the emergency department, the triage nurse assesses vital signs and gathers information from the patient to determine the severity of their condition. This aims to provide appropriate medical intervention quickly for life-threatening cases and minimize waiting times for less critical cases, thus contributing to the efficient allocation of scarce resources. Our study aimed to evaluate the triage knowledge, skills, and practices of emergency nurses in Mafraq, Jordan. MethodsA cross-sectional study used a previously validated questionnaire. Fifty emergency nurses from two public and one private hospital in Mafraq participated. We collected data through an online survey then analyzed in SPSS. Results92% of nurses had sufficient triage knowledge ([&ge;]60%), while 14% exhibited deficient triage skills (<60%) and 86% had moderate skills (60-80%). Regarding practices, 32% rated as "poor" (<60%) and 68% as "adequate" (>60%). Length working in emergency, hospital type significantly related to nurses triage knowledge, skills, and practices. ConclusionThe study underscores continual trainings, simulation programs and mentorships importance for enhancing emergency nurses triage knowledge, skills, especially in rural settings. Implementing clear triage protocols, continuous support and integrating triage competencies into curricula are recommended to improve overall triage competency

BackgroundProlonged wakefulness, restricted sleep, and circadian factors can impact driving performance and road safety. Currently, there are no effective objective roadside tests to detect the state of drivers sleepiness during or prior to driving, or predict future driving impairment risk. This paper reports on an extended wakefulness protocol used to determine if a portable virtual reality device to administer vestibular-ocular motor function (VOM) tests can effectively detect 1) drivers state of sleepiness during or just prior to driving, and 2) predict trait sleepiness and future driving risk. MethodsFifty healthy adults with regular sleep within 9pm to 8am were recruited for an experimental laboratory procedure which involved two phases: an initial overnight sleep study, and a subsequent period of extended wakefulness lasting ~29 hours. During the wakefulness phase, participants undertook neurobehavioural testing, a simulated driving test, and repeat assessments of VOM to establish if ocular markers can predict sleepiness state and sleepiness-related performance impairments (Trial registry ACTRN12621001610820). DiscussionThis protocol outlined a study that aimed to establish the sensitivity of VOM test the effects of extended wakefulness and circadian phase on driver state and trait sleepiness and subsequent sleepiness-related driving impairment. Furthermore, the protocol aims to define the best VOM predictors to identify driver sleepiness state (road side testing and pre-drive assessments) and sleepiness trait (predicting future driving risk) to establish proof of concept for its potential application as a roadside, pre-drive and general sleepiness related fitness to drive test.

IntroductionMusculoskeletal injuries (MSKIs) are ubiquitous in the U.S. military, especially among high-performing service members such as Marines. Given that female service members only started to be assigned to ground combat roles since December 2015, evaluation of sex on MSKI risk in ground combat occupations has not been possible until there was an ample population to study. The purpose of this population-level epidemiological study was to assess (1) if female sex was a salient risk factor for MSKI in Marines serving in different military occupations, including combat arms, and (2) the effects of integration period on MSKI risk among female Marines. Materials and MethodsA population-based epidemiological retrospective cohort study of all U.S. Marines was performed assessing female sex, occupation, and integration period on the prevalence of MSKI from 2011 through 2020. The Military Health System Data Repository was utilized to identify initial healthcare encounters for diagnosed ankle-foot, knee, lumbopelvic-hip, thoracocostal, cervicothoracic, shoulder, elbow, or wrist-hand complex injuries. Prevalence was calculated for female and male Marines in each occupational category (combat, combat support, aviators, aviation support, services) during the pre-integration (2011-2015) and post-integration (2016-2020) periods. ResultsDuring the pre-integration period, 520/1,000 female Marines (n=13,985) and 299/1,000 male Marines (n=142,158) incurred MSKIs. In the post-integration period, the prevalence increased to 565/1,000 female Marines (n=17,608) and 348/1,000 male Marines (n=161,429). In the multivariable evaluation of sex, occupation, integration period, and the interaction of sex and occupation on combined MSKIs, only female sex was a significant factor for injury (prevalence ratio [PR]=1.99), with service in ground combat and aviation occupations identified as protective factors when compared with services occupations (PR=0.69). When these same factors were evaluated for specific MSKI outcomes, female sex remained a robust factor in all lower quarter (PR=1.75-2.63) and upper quarter (PR=1.38-2.36) injuries except for shoulder injuries. Service in ground combat and aviation occupations was protective for all lower quarter injuries (PR=0.46-0.71). In the upper quarter, ground combat was protective for all injuries except for elbow injuries (PR=0.67-0.77). Serving as an aviator was a risk factor for cervicothoracic (PR=1.57) and thoracocostal (PR=1.22) injuries and a protective factor for shoulder (PR = 0.73) and wrist-hand (PR = 0.46) injuries. Adjusted risk for lumbopelvic-hip (PR=1.13), ankle-foot (PR=1.53), cervicothoracic (PR=1.19), thoracocostal (PR=1.14), and elbow (PR=1.48) injuries significantly increased during the post-integration period. There was a significant sex-by-period interaction for shoulder injuries alone, with female sex in the post-integration epoch found to be salient (PR=1.26). ConclusionsFemale sex was a salient factor for MSKI, with service in ground combat and aviation occupations identified as protective factors when compared with services occupations. In the evaluation of specific MSKIs, female sex remained a robust and significant factor in all lower quarter injuries and upper quarter injuries except for shoulder injuries. There was only a significant sex-by-period interaction for shoulder conditions, with an increased risk of these injuries in female Marines in the post-integration period.

1.AI is already finding its way into the diagnostic radiology realm of various regions around the world, but there is still a lack of evidence on the situation in LMICs. This qualitative study examined the research problem through the perspectives of clinicians regarding the adoption of AI-Radiology in Karachi, Pakistan, using the Technology Acceptance Model and interpreting the results into practice and policy using the Problem Driven Iteration Adaptation lens. 13 clinicians (radiologists, tertiary care hospitals) were interviewed between May and August 2025. The semi structured interviews were audio recorded, transcribed and coded in NVivo 14. TAM constructs of perceived usefulness and perceived ease of use were analyzed in a deductive content analysis, and interpretation of implementation pathways was informed by PDIA. Four themes emerged. Implementation attitudes were realistic optimism. The subjects put AI in terms of an assistant and second reader, and clinical judgment and accountability could not be delegated. Issues centered on privacy of data, and over dependence. Perceived ease of use was based on training, infrastructure, fit in workflow and trust. Costs, poor connectivity, the lack of institutional capacity, and generational resistance were the barriers whereas triage acceleration, mass screening support, workload reduction, and time saving were the facilitators. For adoption, education, practical upskilling, guidelines, and local clinical approval were requirements. The greatest perceived usefulness was in situations where AI was applied to specific bottlenecks like quick screening, quantitative measurements, remote-area reporting, and trainees decision support; the constraints included data quality, generalizability, and algorithm error, the risk of confidentiality, and the impossibility to substitute contextual clinical reasoning. Such priorities as national and institutional data protection policies, formal vetting of tools, smooth integration with radiology information systems and AI literacy in the curriculum were included. The sample is limited to one city and the qualitative design does not enhance generalizability but the results provide practical recommendations. The mixed resource setting of Karachi is a potential place where AI can be a reliable collaborator in the field of radiology in case of adequate infrastructure and training of clinicians and a long-term human control. Perceived usefulness can be converted to routine and safe clinical use with strategic and staged implementation.

BackgroundHip fracture remains a leading cause of morbidity and mortality among older adults in the United States. The aim of this systematic and meta-analytical review is to synthesize available evidence on predictors of one-year mortality following hip fracture among older adults, guided by a socio-ecological framework. MethodsWe searched PubMed, Embase, Web of Science, CINAHL, and Scopus for U.S.-based studies published between 2010 and 2025 reporting one-year mortality after hip fracture. Studies were included if they evaluated predictors of mortality across pre-injury, perioperative, or post-discharge phases. Data were extracted on study design, population characteristics, mortality outcomes, and risk factors. Predictors examined in [&ge;]3 studies were pooled using random-effects meta-analysis, and narrative synthesis was conducted for predictors with limited data. Methodological quality was assessed using the Joanna Briggs Institute checklist. ResultsTwenty-eight studies (n = 835,226) met inclusion criteria. Pooled one-year mortality was 21.8%, ranging from 7.1% to 54.4%. Advancing age and male sex were consistent non-modifiable risk factors. Comorbidity burden, including congestive heart failure, chronic kidney disease, myocardial infarction, and dementia, and measures of frailty and functional impairment were among the strongest predictors, often doubling mortality odds. Perioperative factors such as higher injury severity and delayed surgery, and post-discharge factors including hospital readmission, missed follow-up visits, and postoperative complications, were also associated with increased mortality. ConclusionOne-year hip fracture-related mortality remains high and stems from multifactorial causes. A multi-level, systems-oriented approach may be necessary to meaningfully reduce long-term mortality in this growing and vulnerable population.

BackgroundA Hospital Medicine Advanced Practice Provider (HMAPP)-led care model developed in response to the high acuity and increased patient volumes associated with the Covid-19 pandemic. Although anecdotally perceived as a successful model, questions remained if there was adequate pre-planning and formal implementation strategy for stakeholder buy-in. ObjectiveTo elicit HM physicians and APPs perceptions of the HMAPP-led care model implementation and consider necessary steps for optimal future APP care model development and operation. Design, Setting and ParticipantsThis qualitative study used 10 (5 physicians and 5 APPs involved in the care model pre- and post-implementation) individual semi-structured, virtual interviews based on the Consolidated Framework for Implementation Research (CFIR). Deductive and inductive rapid analysis was utilized to analyze the data. ResultsTwo themes emerged as strengths: 1) Experienced APPs delivered the care model, 2) Acceptance of the care model evolved over time. Four themes suggested opportunities for future development: 1) Guidelines should expand from patient distribution to include minimal collaboration and escalation expectations, 2) Culture change was a barrier to model implementation and acceptance, 3) Intentional collaboration between APPs and Physicians is necessary, 4) Investment in standardized onboarding enhances buy-in of the care model. ConclusionThe impact of an APP care model can be elevated if implemented with key principles and strategies. This is critical in an evolving health care landscape where all providers need to collaborate and practice with their full expertise to maximize safe, efficient and quality patient care.

Background Older adults' walking has so far been evaluated using standardised assessments of walking capacity within a clinical setting. By taking the evaluation out of the laboratory into the real world, this study provides first evidence of the ability of Digital Mobility Outcomes (DMOs) to detect changes over time and the Minimal Important Difference (MID) in patients after proximal femoral fracture (PFF). This will guide the implementation of DMOs in research and clinical care. Methods For this multicenter prospective cohort study, 381 community-dwelling older adults were included within one year after sustaining a PFF and assessed at two time points, separated by six months. Walking activity and gait DMOs were measured using a single wearable device worn on the lower back for up to seven days. A global impression of change question and three mobility-related outcome measures (Late-Life Function and Disability Instrument; Short Physical Performance Battery; 4m gait speed) were used as anchor variables. To assess each DMOs ability to detect changes, we calculated the standardized mean change as effect size. For estimating MIDs, both distribution-based and anchor-based methods were applied, followed by triangulation by experts if at least three anchor-based estimates were available per DMO, resulting in single-point estimates. Results All three anchor variables demonstrated substantial changes. Overall, 10 out of 24 available DMOs showed large and 7 DMOs moderate positive effects in the expected direction of the respective anchors. Seven DMOs showed no or only small effects. For 12 DMOs, at least three anchor-based estimates were available, enabling MID triangulation. MIDs for walking activity DMOs per day were: a walking duration of 10 minutes, a step count of 1,000 steps, 50 walking bouts (WB), and 15 WBs in WBs over 10 seconds. For gait DMOs, depending on the walking bout length, MIDs for walking speed were between 0.04 m/s and 0.08 m/s, and MIDs for cadence between 4 and 6 steps/minute. Almost all DMOs showed a strong ability to detect improvement in mobility, but rarely in detecting decline. Conclusions For the first time, MIDs are presented for real-world DMOs in PFF patients. These MIDs inform sample size requirements and interpretation of intervention effects for clinical trials, thereby providing guidance and reassurance for clinicians and regulatory bodies.

BackgroundDementia affects over 57 million people worldwide. UK and international policy position personalised, conversation-based care planning as central to post-diagnostic support. However, delivery in primary care is inconsistent, and many practitioners lack dementia-specific communication training. Existing evidence focuses on single roles or settings, leaving a gap in understanding how communication operates across the primary care workforce. AimsTo identify what helps and hinders effective communication for integrated dementia care planning and determine the support and training needs of the wider primary care workforce. MethodsO_LISemi-structured interviews - 11 people with dementia, 13 family carers, and 19 primary care practitioners from diverse roles, exploring experiences of care planning conversations C_LIO_LIReflexive thematic analysis C_LI ResultsThree themes were developed, progressing from micro-level communication practices (Theme 1: Beyond the tick-box), through triadic dynamics (Theme 2: Balancing voices in the conversation), to organisational influences (Theme 3: From silos to meaningful shared care planning). Time and Conversation as intervention cut across all themes, shaping trust and disclosure. Participants reported reliance on tick box approaches, inconsistent preparation, and uncertainty about care plan purpose and ownership. Non-clinical roles were commonly viewed as well placed to support meaningful conversations, but were often described as constrained by unclear remit and weak integration. ConclusionsA persistent gap remains between policy ambitions and everyday practice. Time-pressured, checklist-driven encounters and fragmented systems undermine shared decision-making. The expanded primary care workforce offers untapped potential to address these gaps, but this requires clearer roles, formal integration, and targeted investment in communicative skills.

ObjectivesNon-communicable diseases (NCDs) account for almost 90% of deaths in Europe, yet comparative estimates of the productivity costs associated with premature NCD mortality across diseases and countries remain limited. This study estimates and compares productivity losses attributable to cardiovascular disease (CVD) and cancer mortality among working-age populations across Europe. Population-based data were used to estimate productivity costs for CVD and cancer deaths across 30 European countries. Sex- and age-specific mortality data for 2021 were obtained from the World Health Organization Mortality Database. Economic data, including wages, unemployment rates, and labour force participation rates, were sourced from Eurostat. Productivity losses were valued using a human capital approach incorporating an age-transition lifecycle simulation model that adjusts for lifetime wage trajectories and labour market dynamics. Costs were discounted at 3.5%. Total productivity losses from cancer and CVD mortality in working-age populations were estimated at {euro}195.7 billion, equivalent to 1.24% of European GDP. Cancer accounted for 62.5% ({euro}122.2 billion) of total productivity losses, while CVD accounted for 37.5% ({euro}73.5 billion). Total CVD-related productivity costs exceeded cancer-related costs in Central and Eastern Europe, whereas cancer productivity costs were higher in Western, Northern, and Southern Europe. Mean productivity costs per death were higher for CVD ({euro}219,848; 95% CI 165,241-270,247) than for cancer ({euro}217,744; 95% CI 166,554-273,144). A larger gender gap was observed for CVD mortality, with a male-to-female cost ratio of 2.5 compared with 1.6 for cancer. Productivity losses associated with premature cancer and CVD mortality represent a substantial economic burden across Europe, with pronounced variation by disease, region, and sex. These findings provide comparative, cross-country estimates of the human capital costs associated with major NCD causes of death.

Good leadership is a crucial aspect for a good primary healthcare system and for enhancing patient health outcomes. This qualitative exploratory study sought to explore the leadership role played by family medicine registrars in bedside teaching at Mangochi District Hospital and Nkhoma Mission Hospital in Malawi. Focus group discussions were held with healthcare workers who worked under the registrars, and the data was analyzed qualitatively using inductive and deductive analysis. From the study, it was established that the registrars have good clinical leadership skills, including working in collaboration, mentorship, ethical behavior, flexibility, and resourcefulness. However, the effectiveness of the leadership role is limited by a lack of clear role boundaries, mentorship, limited participation in system decision-making, and a lack of feedback. The family medicine registrars demonstrated high levels of interpersonal and professional competencies, which have a high potential for improving leadership roles. The study has provided useful insights on how the leadership training in the Master of Family Medicine course at Kamuzu University of Health Sciences (KUHeS) can be improved.

BackgroundThis study aims to explore disparities in telemedicine research, investigate the impact of the COVID-19 pandemic on these inequalities, and examine the association between various socioeconomic factors and telemedicine research output across Low- and Middle-Income Countries (LMIC) and High-Income Countries (HIC), and World Health Organization (WHO) regions. MethodsA comprehensive search strategy was developed to identify telemedicine-related documents (2018-2022) in Scopus and SciVal, with false positives and negatives resolved. Mann-Whitney U and Wilcoxon Signed Rank tests compared publication volume and Field-Weighted Citation Impact (FWCI). A novel metric, Research Interest (RI), was calculated by dividing telemedicine publications by total outputs in medicine and life sciences. WHO regions were ranked using TOPSIS. Spearman Rank Correlation assessed links between socioeconomic variables and research output separately in HIC and LMIC. Analyses were conducted using R (v4.3.2). ResultsWe retrieved 16,584 telemedicine-related articles: 4,244 from 58 LMIC and 13,622 from 47 HIC, including 1,282 collaborative publications (30% of LMIC and 9.4% of HIC outputs). HIC consistently produced more publications than LMIC. While FWCI differences were significant in the pre-COVID era (Cliffs Delta = 0.48), no significant difference was observed post-COVID. RI for telemedicine showed no significant difference between HIC and LMIC in any timeframe. The Western Pacific led in quality metrics, while the Americas ranked highest overall. Southeast Asia ranked lowest in both. Exclusively among HIC, Health Expenditure (Purchasing Power Parity adjusted) (r = 0.63, r = 0.45) and Human Development Index (r = 0.50, r = 0.47) were moderately, and ICT service exports (USD) (r = 0.72, r = 0.33) were strongly correlated with both telemedicine scientific output and RI. ConclusionGlobal inequalities in telemedicine research favor HIC, though the gap narrowed post-COVID. Among HIC, telemedicine research patterns more proportionately reflect socioeconomic indicators, research capacity, infrastructure, and domestic health needs.

Abstract Background: Enhanced Recovery After Surgery (ERAS) optimizes perioperative management for colorectal cancer (CRC), improving short-term outcomes, but its impact on long-term outcomes remains inconclusive, supporting the need for this meta-analysis. This study evaluates the effect of perioperative ERAS (therapy-focused) on 1-, 2-, 3-, and 5-year postoperative survival in patients with CRC. Methods: We conducted a systematic review and meta-analysis following a pre-registered protocol in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed, Web of Science, Embase, Medline Ovid, and Cochrane Library Wiley were searched up to December 31, 2025, for clinical studies reporting long-term postoperative survival outcomes of patients with CRC undergoing ERAS implementation. Of 1,063 retrieved reports, 10 studies (5,876 patients) were included in Kaplan-Meier-based meta-analyses and eight studies (5,556 patients) in aggregated data meta-analyses. Data extraction was performed independently by two reviewers, with study quality and risk of bias assessed using the Newcastle-Ottawa Scale (NOS) and RevMan software. Effect sizes were pooled using fixed-or random-effects models according to heterogeneity, with cross-validation and subgroup analyses examining the influence of tumor stage and ERAS adherence. The pre-specified primary outcome was postoperative overall survival (OS) [&ge;]12 months, and the secondary outcome was disease-free survival (DFS). Results: ERAS significantly improved OS at 1 year (93.2%, 95% CI: 92.3-94.2 vs. 90.2%, 95% CI: 89.1-91.2), 2 years (86.7% vs. 81.3%), 3 years (81.1% vs. 72.4%), 5 years (70.9% vs. 60.6%) (all P<0.01). The pooled HR for mortality was 0.72 (95% CI: 0.63-0.83, P<0.01), indicating a 28% reduction in long-term mortality. Stage I-II tumors and ERAS adherence [&ge;]70% conferred the greatest benefits. DFS did not show a statistically significant improvement (HR=0.90, 95% CI: 0.68-1.19, P=0.45). Included studies were of moderate to high quality (NOS score 6-9). Conclusions: Perioperative ERAS significantly improves 1- to 5-year OS and reduces long-term mortality in patients with CRC, with the greatest benefits in early-stage disease and high adherence. These findings support ERAS as a critical component of comprehensive CRC care.

Childhood malnutrition remains a major public health challenge in Ethiopia, where stunting and wasting co-exist but may arise from distinct spatial and etiological processes. Analyses focusing on a single outcome may overlook the interdependence of these conditions and their geographic heterogeneity. This study aimed to disentangle the determinants of stunting and wasting among children under five years of age using a Bayesian bivariate spatial modelling framework. Data from 5,405 children included in the 2019 Ethiopia Mini Demographic and Health Survey were analyzed. Stunting and wasting were modelled as correlated binary outcomes using Bayesian bivariate hierarchical geostatistical models implemented through SPDE-INLA, accounting for child, maternal, household, and environmental covariates, non-linear age effects, and spatial dependence. Model performance was assessed using the deviance information criterion, Watanabe-Akaike information criterion, and marginal log-likelihood. The bivariate model identified shared socio-economic and biological determinants. Multiple births, male sex, low maternal education, a higher number of under-five children, and household poverty were associated with increased risks of both outcomes. Female-headed households were associated with lower odds of stunting but higher odds of wasting. Spatial analysis revealed elevated residual stunting risk in the northern and central highlands, whereas wasting hotspots were concentrated in northeastern pastoralist regions. Residual spatial correlation was weak ({rho} = -0.12), indicating largely independent geographic patterns. These findings suggest that effective child nutrition policies in Ethiopia require outcome-specific and regionally tailored interventions addressing both chronic and acute forms of malnutrition.

Artificial intelligence (AI) is increasingly integrated into healthcare delivery, yet patient acceptance in resource constrained settings remains incompletely characterized. This study assessed attitudes toward AI supported care among patients attending hospitals in three Jordanian governorates (Amman, Balqa, Irbid) and examined demographic and digital literacy correlates of acceptance. In a cross sectional survey (n = 500 complete questionnaires), participants rated exposure to AI in healthcare and five attitudinal domains, namely perceived usefulness or performance expectancy, trust and transparency, privacy and perceived risks, empathy and human interaction, and readiness or behavioral intention, using 25 items on 5 point Likert scales. Patients expressed conditional optimism: empathy and human interaction was most strongly endorsed (M = 4.33, SD = 0.58), alongside relatively high perceived usefulness (M = 3.97, SD = 0.68), while trust and transparency (M = 3.57, SD = 0.74) and readiness (M = 3.66, SD = 0.90) were moderate to high; privacy and risk concerns were moderate (M = 3.51, SD = 0.77) and self reported exposure was lowest (M = 2.57, SD = 1.07). The highest agreement item indicated preference for AI to work alongside physicians rather than be relied on alone (M = 4.47, SD = 0.81). Trust and transparency and perceived usefulness were positively associated with readiness (r = 0.48 and r = 0.44, respectively; p <.001), while privacy and perceived risks were negatively correlated with trust and usefulness. In multivariable regression adjusting for gender, age group, education, prior AI health app or device use, and self rated digital skill, lower educational attainment (less than high school and high school) predicted reduced readiness, whereas higher digital skill predicted increased readiness (R2 = 0.101). These findings suggest that implementation strategies in Jordan should emphasize human involvement alongside AI, transparent communication and governance, and interventions that build digital confidence and reduce readiness gaps linked to education. Author summaryAI is increasingly used in healthcare, for example to support diagnosis, triage, and treatment decisions. Whether these tools are accepted by patients depends not only on how well they work, but also on whether patients trust them, understand how they are used, and feel their privacy is protected. Evidence on patient views in middle income and resource constrained settings is still limited. We surveyed 500 patients attending hospitals in three Jordanian governorates to understand how they view AI supported care. Patients generally expected AI to be useful, but they strongly preferred that clinicians remain actively involved and that AI supports rather than replaces physicians. Trust and perceived usefulness were closely linked to willingness to accept AI enabled care, while privacy concerns were present and shaped trust. Readiness to accept AI was lower among participants with lower educational attainment and higher among those with greater self rated digital skill. These findings suggest that successful implementation in Jordan should prioritize transparent communication, strong privacy safeguards, and human centered workflows, while also strengthening digital confidence to avoid widening gaps in acceptance.

BackgroundThe accelerating pace of urbanization worldwide has highlighted the improvement of disaster response in cities as a global priority. Yet, there remains a poor understanding of the emergency response to mass casualty incidents (MCI) in these environments. This study aimed to develop a conceptual framework for cities responses and potential policy levers. MethodsWe conducted a scoping review followed by in-depth interviews (IDIs), focus group discussions (FGDs), and a modified Delphi process to develop the framework for Cities Assessment of Mass Casualty Emergency Response and Action (CAMERA). ResultsCAMERA framework consists of six essential components of urban emergency response systems: 1) communication, 2) safety and security, 3) human resources, 4) policy and plans, 5) command control and coordination, and 6) care delivery. IDIs and FGDs also provided insight on assessment methodologies for evaluating response capacity. Using these components, we then developed a framework consisting of a diagnostic and management approach that city leadership can undertake in MCI management to ensure effective functioning at various levels of incident response. ConclusionThe CAMERA framework offers novel and simplified guidance to policymakers and other stakeholders in their attempt to improve MCI response systems across cities globally.