Sustainability

OBJECTIVE To examine parents perceptions regarding the introduction of a social media ban for children and to identify factors associated with these attitudes. METHOD A cross-sectional study was carried out in Greece in April 2026. Potential predictors of parents views on a social media ban included (a) sociodemographic variables (such as gender, age, educational attainment, and financial status), (b) social media usage patterns (number of accounts, daily usage duration, and posting frequency), and (c) level of political engagement (how often participants follow political news and discuss political issues). Outcome variables comprised parents agreement with the ban, level of awareness about its implementation, perceived necessity for additional measures, confidence in the ban effectiveness, perceived effects on children lives, and parents familiarity with digital parental control tools. RESULTS Overall, 68.0% of parents supported implementing a social media ban for children under 15. A large majority (91.8%) expressed the need for more governmental information regarding the ban. Additionally, 89.3% believed that further measures beyond the ban are required to effectively address the issue. Suggested measures included digital literacy courses in schools (86.1%), active parental involvement in digital literacy (74.6%), prohibition of inappropriate content (77.9%), reasonable parental limits on social media use (73.8%), and restriction of addictive platform features (73.0%). Older parents demonstrated greater confidence in the effectiveness of the ban. Furthermore, age, financial status, number of social media accounts, and time spent online were positively associated with perceived impacts of the ban. Younger age was linked to greater parental familiarity with digital control tools, while having more social media accounts was also positively associated with such familiarity. CONCLUSIONS There is a clear need for comprehensive, evidence-based policy approaches that combine regulation, education, and shared responsibility among stakeholders. Policymakers should leverage existing public support for child protection while investing in digital literacy initiatives, empowering parents, and strengthening regulatory oversight of social media platforms to achieve long-term and equitable results.

Greenspace has been associated with a wide range of health outcomes and conditions related to functional limitation and disability. Yet less is known about how the spatial morphology of greenspace relates to disability prevalence across different stages of the life course. This study examines associations between greenspace morphology and disability prevalence among children, working-age adults, and older adults in urban census tracts across the contiguous United States. Using national land-cover data, we quantified morphological metrics at the census-tract level, including greenspace percentage, density, mean size, connectedness, shape complexity, inter-greenspace distance, and diversity. These indicators were linked with age-specific disability prevalence obtained from the American Community Survey. Spatial lag regression models were used to account for spatial dependence while adjusting for socio-demographic and contextual characteristics. Across age groups, higher greenspace percentage was consistently associated with lower disability prevalence (children: {beta} = -0.081, 95% CI: -0.096 to -0.066; adults: {beta} = -0.804, -0.858 to -0.750; older adults: {beta} = -1.132, -1.250 to -1.013). Among children, patch density ({beta} = -0.045, -0.061 to -0.029), mean patch area ({beta} = -0.029, -0.040 to -0.018), connectedness ({beta} = -0.051, -0.069 to -0.032), diversity ({beta} = -0.036, -0.051 to -0.020), and inter-greenspace distance ({beta} = 0.056, 0.039 to 0.073) were all associated with disability prevalence, whereas shape complexity was not ({beta} = 0.004, -0.010 to 0.018). Among working-age adults, associations were observed for mean area ({beta} = -0.023, -0.090 to -0.002), connectedness ({beta} = -0.127, -0.243 to -0.011), shape complexity ({beta} = -0.123, -0.174 to -0.072), diversity ({beta} = -0.146, -0.201 to -0.091), and inter-greenspace distance ({beta} = 0.151, 0.059 to 0.242), whereas patch density was not significantly associated with disability prevalence ({beta} = -0.013, -0.048 to 0.022). In older adults, all examined greenspace morphology metrics showed significant associations with disability prevalence, including patch density ({beta} = -0.445, -0.842 to -0.049), diversity ({beta} = -0.126, -0.188 to -0.065), and inter-greenspace distance ({beta} = 0.455, 0.409 to 0.501). Overall, the findings suggest that higher greenspace percentage, larger patch size, greater connectedness, greater diversity, and more spatially clustered greenspace distributions are associated with lower disability prevalence across the life course, although the strength and consistency of these associations varied across age groups. The study provides national-scale evidence for incorporating greenspace morphology into urban planning and public health strategies to support more inclusive and health-supportive urban environments.

Effective group work is central to Problem-Based Learning (PBL) in higher education, yet the optimal strategy for forming student groups remains unclear. This study compared MBTI based grouping, informed by personality types and Keirsey temperaments, with Learning Style Based (LSB) grouping, grounded in Kolbs Experiential Learning Theory, to assess their impact on group functioning and role performance. Participants were undergraduate students enrolled in Cell Biology (Fall 2022 and Fall 2023) and Introduction to Biology Laboratory (Fall 2023) courses. Students completed MBTI and Kolb Learning Style assessments, and groups and roles (Leader, Communicator, Organizer) were assigned accordingly. Results indicated that LSB-based groups consistently outperformed MBTI-based groups across multiple performance metrics, including productivity, listening, sense of safety, belonging, and overall satisfaction. All metrics showed statistically significant decreases in MBTI based groups except contribution, which did not differ significantly between grouping strategies. Role performance ratings were significantly higher for Leaders and Communicators in LSB groups, while no significant differences were observed for the Organizer role. Correlation analyses revealed that satisfaction was strongly associated with perceived productivity in MBTI based groups, whereas in LSB based groups, satisfaction was more strongly correlated with psychological safety. These findings suggest that learning style alignment may better support effective collaboration and group climate in PBL settings than personality based grouping.

The focus was on leadership, mentoring and promotion. Using short, structured activities alongside small-group discussion, the participants were encouraged to reflect on leadership, mentoring and the perceived gap between being ready and being recognised for promotion. Descriptive survey findings and free-text reflections highlight the demand for structured peer support, reciprocal mentoring opportunities, and clearer, more transparent promotion processes. Following the event, we performed a structured review of the impact. This highlighted that the workshop participants reported that the event allowed for greater self-awareness into their own leadership approaches, a stronger commitment to purposeful mentoring, and greater confidence and renewed motivation to take concrete steps towards promotion.

Nepal's rangelands provide multiple benefits, including support for pastoral livelihoods and alpine biodiversity, regulation of water and soil nutrients, and sequestering carbon. Climate change and anthropogenic pressures are altering these rangelands, leading to vegetation and biodiversity change. However, national-scale assessments of rangeland change are limited in Nepal. This study quantified rangeland changes at multiple spatial scales and assessed the climatic and non-climatic drivers of rangeland change. About 80.7% of Nepal's high-altitude rangeland (> 2,000m) outside protected areas showed no significant change. Among areas exhibiting significant annual maximum NDVI trends, 383,281 ha (18.6%) showed positive and 14,702 ha (0.7%) showed negative trends, corresponding the ratio of increase in vegetation greenness and decline in vegetation greenness to 26:1. Climate predicted positive trends covered 627,184 ha (30.5%), whereas residual trends caused by non-climatic drivers covered 94,656 ha (4.6%). Climate induced negative trends covered 47,609 ha (2.3%) while residual trends were observed in 6,260 ha (0.3%). Negative trend pixels were concentrated mainly within the 3,000 to 5,000 m elevation band, with Karnali Province recording the highest proportional climate predicted decline in vegetation greenness (3.4%). At the municipality scale, rangeland change showed no significant relationship with grazing pressure derived from gridded livestock data, suggesting that grazing pressure alone did not explain the non-climatic vegetation signal. These spatially explicit, nationally consistent results identify where rangeland change is occurring and help distinguish climatic and non-climatic drivers of rangeland vegetation change, providing evidence to support targeted rangeland management under Nepal's federal governance structure.

Although a strand of scholarship on pandemic prevention flourished in the wake of the COVID-19 pandemic, a theoretically informed empirical analysis of global governance entrepreneurs and practitioner perspectives is lacking. This gap is salient given the need to consider the nuances, political realities, and feasibility of real-world governance practice, particularly with the recent adoption of the Pandemic Agreement under the World Health Organisation. In this paper, nexus governance and regime complex theory guides an analysis of recommendations for potential real-world governance responses for pandemic prevention from wildlife trade for human consumption elicited from global governance entrepreneurs and practitioners through semi-structured interviews and document analysis. Recommendations on future governance practice largely focused on strengthening coordination across various policy sectors to improve use of existing institutional arrangements, with particular emphasis on better integration of the biodiversity conservation policy sector within global pandemic prevention governance, as well as reform of the World Organisation for Animal Health and the Convention on International Trade in Endangered Species of Fauna and Flora. With governance deficits for prevention of pandemics emerging from the wildlife trade left by the now largely concluded Pandemic Agreement, a renewed research agenda on shared governance pathways becomes paramount.

Background: Climate change is an escalating global health threat, with sub-Saharan Africa disproportionately affected due to entrenched spatial inequalities, high exposure to environmental hazards, and limited adaptive capacity. Increasingly frequent extreme weather events (EWEs), including floods and cyclones, are reshaping the material and social conditions of place, with implications for mental health and wellbeing. However, evidence remains limited, particularly multi-country qualitative research that examines how mental health impacts are produced through lived experiences of place in contexts of recurring environmental disruption and structural vulnerability. This study explored the mental health and wellbeing impacts of EWEs among individuals with lived experience of such events in Mozambique, Burkina Faso, South Africa, and Kenya, using participatory methods that centred community narratives and place-based accounts of everyday life. Methods: This qualitative study employed digital storytelling as a participatory visual method to examine how EWEs are experienced and narrated across diverse socio-spatial contexts. A total of 37 participants (8 to 10 per country) were recruited from rural, peri-urban, and informal urban settlements with recent exposure to flooding or cyclone events. Participants produced digital stories during facilitated five-day workshops. These narratives were analysed using inductive and deductive thematic analysis informed by Braun and Clarke's framework, with attention to the spatial and relational production of distress and coping. Results: Across Mozambique, Burkina Faso, South Africa, and Kenya, findings show that the mental health impacts of EWEs are deeply embedded in place-based conditions and are cyclical, cumulative, and relational rather than confined to discrete disaster events. Participants described how repeated environmental disruptions reconfigured everyday life in place, generating ongoing uncertainty, anticipatory anxiety during rainfall periods, and acute fear during floods and cyclones. Loss of housing, livelihoods, infrastructure, and social anchors of place contributed to enduring psychological distress, which was frequently reactivated by subsequent environmental cues such as heavy rain, wind, and deteriorating physical environments. Persistent anxiety, hypervigilance, sleep disturbance, and emotional distress were reported across all sites. While social and community networks constituted critical infrastructures of care within place, these were often simultaneously overwhelmed as entire communities experienced shared disruption. Limited and delayed institutional responses further compounded spatial and social precarity. Conclusions: This study provides a comparative participatory account of how EWEs shape mental health through their embeddedness in place across diverse sub-Saharan African contexts. The findings demonstrate that psychological distress is produced through the interaction of repeated environmental exposure, structural inequality, and disrupted place-based infrastructures of daily life, rather than emerging solely as a post-disaster outcome. These results underscore the need for climate-responsive mental health and psychosocial support that is integrated into place-based disaster risk governance, alongside strengthened social protection and community infrastructure that can sustain wellbeing in contexts of recurring environmental instability.

Premise: Rapid and accurate plant species identification is a critical challenge exacerbated by the taxonomic impediment. Although portable near-infrared (Micro NIR) spectroscopy represents a promising solution, the current absence of standardized protocols and a fundamental understanding of how critical acquisition and analysis parameters influence accuracy remain significant barriers. This study focused on the systematic optimization and validation of a comprehensive workflow designed to maximize the reliability of plant identification using this technology. To ensure methodological robustness across diverse foliar matrices, four vascular plant species were strategically selected as a representative test set to encompass morphological extremes, including significant variations in leaf thickness, pubescence, and surface texture. Methods: Using a portable spectrometer on herbarium specimens (exsiccate) of four vascular plant species, we systematically tested five spectral backgrounds, seven pre-processing methods, and four classification models. Subsequently, we optimized the number of spectral readings and evaluated the influence of the leaf scanning surface (adaxial vs. abaxial) on model accuracy. Results: The highest-performing combination was a Shiny Aluminum background, Second Derivative pre-processing, and a Random Forest model, which achieved a mean cross-validated accuracy of 99%. An average of just three spectral readings from the adaxial (upper) leaf face was sufficient to saturate model performance, proving statistically superior to other approaches (p < 0.001). Discussion: This study establishes a validated, high-accuracy protocol for plant species identification from herbarium specimens using portable NIR, offering a powerful tool for biodiversity studies. Direct applicability to fresh plants in the field requires future validation to account for the spectral influence of moisture variability.

Tropical dry evergreen forests (TDEFs) are a unique and highly threatened forest type of the dry tropics. Their restoration could be strengthened if native species demonstrate carbon sequestration comparable to widely used non-native trees. We assessed biodiversity and carbon sequestration in a restored TDEF in India, developed over 50 years from a largely barren landscape. The site now supports high woody-plant diversity, with 91 native species across 34 families. Aboveground biomass (AGB) averaged 66.91 +/- 41.2 Mg/ha comparable to seasonally dry tropical forests globally. Although native species were planted more recently and are shorter than non-natives, they contributed 23.86 +/- 23.4 Mg/ha to AGB and show potential for future increases in basal area. Given their comparable wood densities and capacity to attain similar heights, native species are predicted to sequester carbon at levels similar to non-natives in the long term. AGB was unrelated to species diversity. Overall, native TDEF species can achieve carbon storage while maintaining ecological integrity.

Residential greenness has been associated with reduced heat-related illness, yet the specific role of greenspace morphology at the neighborhood scale remains insufficiently understood. This study quantified the relationship between heat-related illness and multiple dimensions of greenspace morphology using an eight year (2016-2023) unbalanced panel dataset comprising 19,021 block group year observations across 2,427 census block groups in Arizona, USA. One meter high resolution National Agricultural Imagery Program aerial imagery was classified to calculate greenspace percentage, number of greenspaces, average size, shape complexity, connectedness, and distantness, at the block group level. We applied conditional spatial autoregressive models with a negative binomial distribution to estimate associations between each morphology metric and yearly heat-related illness counts, adjusting for sociodemographic and geographic covariates. We found higher greenspace percentage, aggregation, shape complexity, connectedness, and density were consistently associated with lower heat-related illness risk. A one standard deviation increases in shape complexity corresponded to a 12.4% decrease in expected heat-related illness counts (IRR=0.876, 95% CI: 0.834-0.921). Similarly, increases in greenspace percentage (14.6% decrease; IRR=0.855, 95% CI: 0.827-0.885), number of greenspace patches (3.7% decrease; IRR=0.963, 95% CI: 0.937-0.990), average size (4.5% decrease; IRR=0.955, 95% CI: 0.923-0.989), and connectedness (5.5% decrease; IRR=0.945, 95% CI: 0.918-0.972) were all protective. In contrast, larger inter greenspace distances were associated with increased heat-related illness risk (6.1% increase; IRR=1.061, 95% CI: 1.033-1.091). Our findings highlight the critical importance of multiple dimensions of greenspace morphology in mitigating heat-related health risks. These results suggest that heat reduction planning with greening initiatives should consider not only the amount of greenspace but also its spatial configuration to maximize cooling and result in health benefits.

Abstract Background Neighborhood socioeconomic disadvantage may contribute to inequities in access to dental care by influencing the geographic distribution of providers. The Area Deprivation Index (ADI) is a validated measure of neighborhood deprivation, but its association with dental workforce availability has not been examined statewide in California. This study evaluated the relationship between neighborhood deprivation and dental provider density across California ZIP Code Tabulation Areas (ZCTAs). Methods We conducted a cross-sectional ecological study of California ZCTAs using publicly available data from the National Plan and Provider Enumeration System (April 2026), the Neighborhood Atlas 2023 ADI, and 2024 U.S. Census population estimates. Active dental providers were linked to ZCTAs and provider density was calculated per 10,000 residents. ADI was aggregated to the ZCTA level using the median ADI national percentile. Negative binomial regression was used to assess the association between ADI and dental provider density, with population included as an offset. Secondary analyses examined California-specific ADI quartiles, dental deserts, and specialist versus general dentist availability. Results The final analytic sample included 1,426 California ZCTAs representing 39,016,384 residents and 37,945 active dental providers. Greater neighborhood deprivation was significantly associated with lower dental provider density. Each one-percentile increase in ADI corresponded to a 1.8% reduction in provider density (incidence rate ratio [RR] 0.9823, 95% confidence interval [CI] 0.9799-0.9847; p < 0.001). Compared with the least deprived quartile, the most deprived quartile had 61% fewer dental providers (RR 0.39, 95% CI 0.34-0.45; p < 0.001). Overall, 15.9% of ZCTAs contained no active dental providers, increasing from 6.8% in the least deprived quartile to 31.1% in the most deprived quartile. Specialist availability demonstrated an even steeper deprivation gradient, with specialist density declining by 86% between the least and most deprived quartiles.

Background: Chronic illness is a major public health concern in Europe, the United States, and other high-income countries, limiting individuals capacity for self-management and health promotion. Empowerment interventions improve health outcomes while reducing healthcare utilization. Aim: This study assessed the feasibility of implementing the Bodyknowledging Program, a broadly applicable health promotion intervention developed in Norway, at the community level in the US to evaluate participants experiences, program components, and self-management outcomes among adults living with chronic illness, and to identify the programs strengths and areas for cultural adaptation to inform its cross-national transferability. Methods: A multi-method feasibility design was used, including a group of participants living with various chronic illnesses. Reflexive thematic analysis was applied to analyze focus group data, examining participants experiences, program components, and outcomes. Facilitators field notes and post-intervention survey data were additional data sources. Results: Three themes emerged through the thematic analysis: (1) acceptability of the BKPs health promotion content and approaches among US participants, (2) implementation of the BKP intervention in a US community context, and (3) demand and ideas for continued implementation. Facilitator field notes identified challenges in implementing the hybrid format. Survey data confirmed that participants strongly agreed that the program enhanced their ability to recognize bodily signs and tolerance limits, manage symptoms, prevent deterioration, and promote their health. Participants reached consensus on the value of the programs content, materials, organization, and communication strategies. Conclusion: The Bodyknowledging Program is feasible and well-suited for implementation in the US. This community-based empowerment intervention leverages existing but unutilized human resources to strengthen self-management and health promotion among people with chronic illnesses across diagnostic categories. Further research across diverse settings is recommended to support broader dissemination.

Objectives Increased risk of childhood obesity up to age six years has been linked to higher maternal allostatic load (AL), the physical manifestation of repeated stress exposure. However, associations are less evident when using psychological stress indicators, and data mainly come from higher income countries. Using psychological and physiological stress markers, this study evaluates maternal stress exposures and child risk of obesity in Peruvian women and their children, ages 5 to 15 years, living in a disadvantaged urban area. Methods Maternal stress exposures included mental distress (12-item General Health Questionnaire scores of 5+ for moderate/high and <5 for no/low distress) and AL (lower/moderate/higher AL assessed from Latent Profile Analysis of hair cortisol, BMI, waist circumference, systolic and diastolic blood pressure). Child outcomes included BMI-for-age and waist circumference-for-age z scores (BAZ and WCAZ). Linear regression analyses were conducted, adjusting for confounders and reported as coefficients and 95% confidence intervals (95% CI). Results Versus mothers with no/low distress, those with moderate/high distress had children with 0.40 (95% CI: -0.66,-0.13) and 0.32 lower (-0.53,-0.11) child BAZ and WCAZ respectively. Versus lower AL mothers, moderate AL mothers had children with 1.15 (0.41,1.88) and 0.74 (0.20,1.28) greater BAZ and WCAZ while higher AL mothers had children with 1.43 (0.95,1.92) and 0.91 (0.50,1.32) greater BAZ and WCAZ respectively. Conclusions Children of mothers with higher AL were at greater risk of overweight or obesity, which may add to the rising burdens of non-communicable diseases in resource-constrained settings as well as the related social, economic, and public health costs.

Introduction: Climate change disproportionately affects disadvantaged communities, yet construction workforce education rarely addresses interconnected pathways linking energy efficiency, nature exposure, and public health. Green-blue infrastructure delivers co-optimized benefits: reducing building energy consumption 15-30% while decreasing heat-related mortality by approximately 3.9% per degree Celsius of urban cooling (Gasparrini et al., 2017) -- epidemiological benchmarks that inform the dose-response functions embedded in the Ecosystem Justice Translator (EJT). This protocol describes, to our knowledge, the first randomized controlled trial evaluating a curriculum intervention designed to develop planetary health competencies and environmental justice awareness among high school students pursuing construction careers. Methods and analysis: This two-arm, parallel-group randomized controlled trial targets enrollment of N=200 high school students (ages 14-18) from construction career pathway programs in the San Francisco Bay Area (over-recruitment target N=250; 25% buffer for attrition). Students are individually randomized 1:1 to intervention (Community-Centered Design curriculum integrating the Ecosystem Justice Translator) or control (traditional Virtual Design and Construction curriculum), stratified by school site using block randomization. The 6-month intervention features the Ecosystem Justice Translator (EJT) -- a computational system using large language models to translate community health equity concerns into quantifiable investment priorities. The EJT's 51-theme health equity taxonomy was derived from validated public health frameworks (Centers for Disease Control and Prevention [CDC] Social Vulnerability Index, Environmental Protection Agency [EPA] EJScreen, Healthy People 2030). Primary outcome is Health-Integrated Equity Consciousness Index (HI-ECI), measured at baseline, 3, 6 (primary endpoint), and 12 months. Analysis uses intention-to-treat linear mixed-effects models with random intercepts for participants. The minimum required sample (n=26 per arm; G*Power, two-tailed a=0.05, 80% power, Hedges' g=0.80) is exceeded by enrolled N=200, which provides >99% power at Hedges' g=0.80 and supports multi-site confirmatory factor analysis. Ethics and dissemination: This protocol has been approved by Stanford University Institutional Review Board (IRB eProtocol #84369, approved February 13, 2026). Parental consent from a parent or guardian and written assent from each student participant are required prior to enrollment. All instruments, curriculum materials, and EJT source code will be released open-source under CC BY-NC-SA 4.0, permitting free use for educational, research, and non-profit purposes, concurrent with primary publication. Commercial licensing may be pursued separately through Stanford University Office of Technology Licensing (OTL docket S25-565). Trial registration: ClinicalTrials.gov NCT07315919. Pre-results. Protocol version 4.0, June 2026.

Socioeconomic, demographic, and health system structures may have shaped COVID-19 pandemic impact across populations, but past analyses typically examined few factors. We systematically examined correlates of COVID-era excess mortality, considering 2,745 county-level variables of demography, race/ethnicity, income, insurance, education, employment, housing, and health system. Pearson correlation coefficients (CCs) were obtained for the most recent available pre-pandemic value against age-standardized county excess-death for each year during 2020-2024. Counties were population-weighted. Variables were grouped by meaning into 11 semantic super-clusters. Overall, 17.3% of variables reached at least a moderate correlation level (|CC| > 0.30) and 2.8% reached strong correlations (|CC| > 0.45). Strongest correlations were seen for college attainment (CC -0.54), uninsurance among adults 40-64 (+0.53), and high income (-0.53). At least moderate correlations were seen for 9.1% of variables in 2020 and 8.5% in 2021, but only 1.8%, 0%, and 1.3% in 2022, 2023, and 2024, respectively. Similar patterns of concentration of moderate correlations in the first two pandemic years appeared in both elderly and non-elderly populations. Of 472 variables with |CC| > 0.30, 362/395 moderate-band and 77/77 strong-band variables belonged to demography and socioeconomic super-clusters. Only 7% of health system variables reached |CC| > 0.30, versus 31% of socioeconomic and demographic variables. Using the most recent available value until 2023 or 2015, different population weighting, and Spearman correlations yielded similar results. Overall, these ecological analyses suggest strong relationships of socioeconomic structure and demographics rather than health-care resources/supply with excess mortality across US counties especially during 2020-2021.

The development of cost-effective, serum-free media is critical for scalable cultivated meat production. This study used high-throughput screening through a Design of Experiments (DoE) approach to develop an animal-free, serum-free medium (MMM1) specifically for the C2C12 murine myoblasts model cell line with applicability in cultivated meat research including for pet food. Low cost, food-grade inputs such as methylcellulose and spirulina extract resulted in significant cell growth improvements. The optimised MMM1 formulation containing low cost, food-grade inputs, achieved cumulative population doublings comparable to 10% (v/v) fetal bovine serum over four consecutive passages. Furthermore, MMM1 supported scalable cell expansion on commercially available dextran-based microcarriers (Cytodex-3) in both static and agitated conditions in spinner flasks, matching growth rates of serum-based controls. Finally, transitioning to a food-grade DMEM/F12 basal medium maintained cell proliferation equivalent to the pharmaceutical-grade DMEM/F12, but at a significantly lower cost, thus offering a viable strategy to substantially reduce biomanufacturing costs which is a critical challenge in cultivated meat production.

Global climate change has increased the frequency and intensity of drought events, making it urgent to understand how native species respond to water deficit (WD). In biodiverse environments such as tropical forests, simple methods are needed to study multiple species simultaneously. This can help predict how natural environments will respond to climate change and guide the strategic selection of drought-resistant species for reforestation. This study aimed to: (1) adapt an existing simple and inexpensive method to apply a controlled WD on tree seedlings from tropical species commonly produced in nurseries for restoration projects, suitable for greenhouse experiments; and (2) evaluate the effectiveness of this method in generating ecophysiological responses to WD that allow the estimation of species' drought resistance. Ten native tree species from the Semideciduous Seasonal Forest (SSF), a phytophysiognomy of the Atlantic Forest, were selected. An existing method was adapted to implement capillary irrigation, in which the bases of the seedling tubes were placed in floral foam blocks positioned inside 15 L plastic containers filled with water. A gradual and severe WD was applied to five seedlings of each species by removing all water from the containers, leaving only the water retained in the saturated floral foam available for plant uptake. The remaining seedlings were maintained well-watered (containers full and foam saturated) as the control group. Stomatal conductance (gs) was measured daily for all seedlings until they reached 50% or less of their initial gs (igs); at this point, stem water potential ({Psi}w) was measured. Both gs and {Psi}w differed significantly among treatments and species (p < 0.01). Ficus guaranitica and Heliocarpus popayanensis were the only species that did not show significant {Psi}w differences between treatments, indicating higher drought resistance. In contrast, Campomanesia xanthocarpa and Eugenia uniflora had the lowest {Psi}w values under WD, suggesting lower drought resistance. The remaining species were distributed along a gradient of responses to WD. Additionally, no correlation was found between {Psi}w and gs at 50% igs in the WD group (rho = 0.16, p = 0.26). The method proved effective in inducing controlled WD and generating measurable ecophysiological responses, offering a useful tool for screening native species for drought resistance.

Health workforce performance is central to service quality, yet little empirical work has examined how performance management systems operate for physiotherapists in rehabilitation services in low- and middle-income settings. This cross-sectional study assessed the current state, perceived effectiveness, and process gaps of performance management systems among physiotherapists working in public rehabilitation centers in Dhaka, Bangladesh. A pretested semi-structured questionnaire was administered to 105 physiotherapists between September and October 2025. Descriptive statistics were used to summarize participant characteristics and performance management indicators. Wilson 95% confidence intervals were estimated for key proportions. A nine-item exploratory performance management system maturity score was constructed from process indicators. Fisher exact tests with Cramer's V were used to examine associations with perceived system effectiveness, and exploratory logistic regression estimated odds ratios for effective or moderately effective performance management. The mean age of respondents was 31.6 years, 56 of 105 were male, and 85 of 105 had graduate or postgraduate qualifications. Formal performance management systems were reported by 102 of 105 respondents (97.1%, 95% CI 91.9-99.0). Standardized appraisal timing and method, assessment form use, performance planning, and formal evaluation systems were each reported by about 60-70% of participants. Reward-performance linkage was perceived as motivating by 97 of 105 respondents (92.4%, 95% CI 85.7-96.1). Overall, 81 of 105 respondents (77.1%, 95% CI 68.2-84.1) rated the system as effective or moderately effective. Training recipient category was associated with perceived effectiveness (Fisher exact p=0.0035; Cramer's V=0.363), as was perceived appropriateness of the process (p=0.0323; Cramer's V=0.258). The maturity score was not independently associated with perceived effectiveness in exploratory regression. Public rehabilitation centers in Dhaka appear to have formal performance management systems, but the systems are only moderately developed. Strengthening training coverage, transparent evaluation criteria, routine feedback, and formal system review may improve staff confidence in performance management processes.

Abstract Background: Despite considerable reductions in under-five mortality during the Millennium Development Goal era, progress towards Sustainable Development Goal (SDG) 3.2 remains uneven across Africa. Identifying countries at greatest risk of missing the target is essential for prioritizing interventions and resource allocation. Methods: A Bayesian spatial forecasting ecological study was conducted using 2024 country-level data from 49 African countries obtained from UNICEF. Spatial dependence was assessed using Global Moran's I and Local Indicators of Spatial Association. Bayesian structured additive regression models with Gaussian, Gamma, and Exponential likelihoods were fitted using Integrated Nested Laplace Approximation (INLA) and compared using the Deviance Information Criterion (DIC), Watanabe-Akaike Information Criterion (WAIC), and conditional predictive ordinates. Posterior exceedance probabilities were estimated, an SDG Failure Index (SFI) and a Priority Intervention Index (PII) were developed, and Bayesian posterior predictive simulations were performed to estimate country-specific probabilities of attaining SDG 3.2 by 2030. Results: Significant spatial clustering of under-five mortality was observed with (Moran's I = 0.355, p < 0.001), and hotspots in Benin, Cameroon, and Nigeria. The Gamma model provided the best fit (DIC = 114.92; WAIC = 111.71). Diarrhoea was the only significant predictor (posterior mean=0.030; 95% credible interval: 0.004-0.056). Twenty-three countries (46.9%) were classified as high risk, whereas only five (10.2%) had achieved SDG 3.2. West Africa recorded the highest mean mortality (7.05%) and North Africa the lowest (1.64%). Bayesian projections indicated that only five countries were likely to achieve SDG 3.2 by 2030, while 41 (83.7%) were unlikely to do so. Conclusion: Considerable geographical inequalities in under-five mortality persist across Africa, and most countries remain off-track for achieving SDG 3.2 by 2030. The integration of exceedance probability mapping, the SDG Failure Index, the Priority Intervention Index, and Bayesian probability forecasting provides a practical framework for monitoring progress and prioritizing countries requiring accelerated action towards achieving SDG 3.2.

Background Timely assessment, classification, and escalation of public health events are essential for effective outbreak response, yet decision-making after event detection remains challenging because of fragmented guidance and variable interpretation of escalation criteria.To strengthen public health emergency management, Kenya developed the Decision-Making Tool for Public Health Emergencies (DMT-PHE), a framework for event assessment, classification, notification, and escalation. An artificial intelligence (AI)-enabled version, the DMT-PHE AI Agent, was subsequently developed to operationalize the framework through decision support. This study describes the development of the DMT-PHE AI Agent and evaluates its performance, usability, safety, and user acceptability. Methods The DMT-PHE AI Agent was developed using a retrieval-augmented generation architecture supported by a curated knowledge base derived from the validated DMT-PHE framework and related public health guidance. A simulation-based pilot evaluation was conducted among 11 public health professionals who independently assessed three standardized outbreak scenarios. AI-generated recommendations were compared with expert-defined gold standards. Outcomes included concordance, response-action coverage, citation performance, safety, usability, and user acceptability. Results Thirty-three scenario evaluations were completed. The AI Agent achieved an overall weighted concordance score of 0.924, with exact agreement of 90.9% for Public Health Events of Initially Unknown Etiology, 81.8% for Rift Valley fever, and 90.9% for Mpox. Citation support was provided in 78.8% of interactions, with no incorrect citations or major safety concerns identified. The mean System Usability Scale score was 85.2, while participants reported high trust (4.27/5), contextual relevance (4.55/5), and perceived time savings (4.82/5). Conclusions The DMT-PHE AI Agent demonstrated that a nationally validated public health emergency decision framework can be successfully translated into an AI-enabled decision-support system. These findings provide early evidence that AI can augment public health emergency decision-making by delivering structured, transparent, and context-specific recommendations while maintaining human oversight, offering a practical model for operationalizing national public health guidance.