Disaster Medicine and Public Health Preparedness

This study aims to map significant cold spots of postacute rehabilitation therapy delivery rates for Original Medicare beneficiaries in the U.S. and determine the prevalence of those cold spots in rural areas. Statistical spatial clustering of postacute therapy delivery rates was conducted in ArcGIS Pro using hot and cold spot analyses (Getis-Ord Gi*). County-level therapy delivery volume was defined as the total minutes of physical, occupational, and speech therapy provided by skilled nursing facilities (SNFs), home health agencies (HHAs), and inpatient rehabilitation facilities (IRFs). Therapy delivery rates were then computed as minutes per Original Medicare beneficiary at the county level and adjusted using a county-level Hierarchical Condition Category risk score. Spatial clustering identified cold spots (statistically significant clusters of low rates) and hot spots (clusters of high rates). We also computed the proportion of cold spots in rural counties and the relative percentage difference compared to the national rural county baseline, using two rural classification systems. Identified coldspots varied by provider type. For SNFs, they were notably identified in the Mountain and West North Central US divisions. For HHAs, cold spots appeared across more U.S. Census Divisions, including areas (e.g., Kentucky, Indiana, southern Illinois) where SNFs showed hot spots. Cold spots were more prevalent in rural--and especially in small rural--counties across all provider types. In rural counties, cold spot rates were 42.8% to 71.5% higher than the rural county baseline. In small rural counties, differences were larger, at 69.1% to 95.5% higher. Concluding, cold spots of postacute therapy delivery varied across the continental U.S. by provider type but were more prevalent in rural and especially in rural counties with smaller population size -- across provider types. Identifying these cold-spot locations may support geographically targeted policy responses and the development of alternative service?delivery models in underserved areas.

The COVID-19 pandemic amplified existing public health emergencies, including the overdose crisis. In rural areas, the effect of emergency preparedness planning on local responses to the pandemic is unknown. We conducted 52 semi-structured interviews with two participant groups (28 people who use drugs [PWUD] and 24 local stakeholders) in two rural counties in southern Ohio. Interviews explored service disruptions, perceptions of the pandemic, organizations pre-existing emergency plans, and communication channels. Transcripts were analyzed thematically to identify data patterns within and between stakeholders and PWUD. Emergency preparedness plans often were inadequate for the needs of PWUD. Several stakeholders reported that their organizations existing plans required updates and additional PWUD perspectives to respond effectively to pandemic-related needs. Both PWUD and stakeholders described widespread service disruptions, including reduced hours, understaffing, and limited access to supplies. Communication was inconsistent, contributing to challenges in maintaining trust and ensuring access to accurate information. Heightened stigma and law enforcement protocols further discouraged the use of essential services. Despite these challenges, PWUD and stakeholders showed resilience and identified community-driven solutions, including peer distribution networks and rapid transition to telehealth services to mitigate these harms. The COVID-19 pandemic exposed critical gaps in existing emergency preparedness plans for PWUD in rural Ohio. Ensuring the continuity of essential services, strengthening communication channels, and integrating PWUD perspectives into future emergency preparedness plans are essential to improve responses to future emergencies.

Background: Academic achievement is crucial for university students, but various factors affect their performance. This study explores the impact of anxiety, sleep quality, social media use, and socioeconomic status on academic performance (CGPA) among public university students in Bangladesh. Data and Methods: Data were collected from 225 students using a structured questionnaire that assessed anxiety (GAD-7), sleep quality (PSQI), social media use (SMUQ), and socioeconomic status (income, parental education). Structural Equation Modeling (SEM) was used to analyze the relationships between these variables. Outcomes: The results showed that socioeconomic status had a strong positive effect on academic performance ({beta} = 0.745, p < 0.001), while anxiety negatively impacted academic outcomes ({beta} = -0.675, p < 0.001). Sleep quality was positively related to academic performance ({beta} = 0.113, p < 0.05), but with a weaker effect. Social media usage is found to have a negative significant effect on academic performance ({beta} = -0.137, p < 0.001). Conclusion: These findings highlight the importance of controlling social media usage and anxiety to enhance academic performance among adult students. Sleep quality and socioeconomic background of the students are also found to be meaningfully associated with their educational progress.

Background: Postpartum Medicaid coverage and support are central maternal health policy issues, but county-level tools for identifying where postpartum Medicaid populations may face overlapping administrative, clinical, and contextual access barriers remain limited. Methods: We developed and internally validated a county-level Postpartum Medicaid Access Barrier Index for all 3,144 counties and county equivalents in the 50 states and District of Columbia. Public data sources included geocoded Medicaid office locations from Shafer et al. (2024), U.S. Census county boundaries, American Community Survey 2024 5-year county indicators, the National Center for Health Statistics 2023 Urban-Rural Classification Scheme for Counties, and county-level hospital-based obstetric care status from the University of Minnesota Rural Health Research Center. Medicaid office locations were spatially assigned to counties, then merged with ACS indicators, rurality, and obstetric care status by county FIPS. The theoretical score range was 0-11; the index assigned higher weights to two core infrastructure measures and lower weights to contextual indicators. Internal validation assessed component structure, known-groups validity, geographic clustering, weighting sensitivity, added value over simpler infrastructure screens, and separation across concern levels. Results: Across 3,144 counties, observed scores ranged from 0 to 10 on the theoretical 0-11 score, with a mean of 3.65 and median of 3. High or highest concern counties accounted for 665 counties (21.2%), including 56 counties (1.8%) in the highest concern group. Component correlations were low-to-moderate, with an average absolute phi of 0.176 and no pairwise component correlation at or above 0.50. Known-groups validity was strong: dual administrative and clinical gap counties scored 4.43 points higher than counties with neither gap (Cohen's d = 3.28, p < 0.001). Scores were geographically clustered (Moran's I = 0.375, permutation p = 0.005). A dual-gap-only screen captured 386 of 665 high/highest concern counties (58.0%) but missed 279 high/highest counties; a parsimonious rule requiring one infrastructure gap plus at least four contextual flags recovered 265 of these 279 missed counties (95.0%) with 100.0% precision. Discussion: The Postpartum Medicaid Access Barrier Index provides a transparent county-level screening tool for identifying places where administrative, clinical, and contextual barriers may overlap for postpartum Medicaid populations and should be externally validated against Medicaid enrollment, renewal, churn, coverage continuity, and postpartum care outcomes.

Objective: To assess the efficacy of an executive peer coaching program, Charting Champions Program (CCP), in helping physicians manage their administrative workload, thereby improving time management, workflow and well-being. Findings: In this longitudinal survey study, physicians self-reported significant improvements in completing charting and administrative paperwork during their clinical day. Physicians reported significant improvements in mental, cognitive and emotional states after the program. Meaning: The Charting Champions Program is an effective intervention that supports physicians in problem-solving the administrative burden of their clinical day, improving workflow efficiency, completing administrative requirements during clinical hours, and enhancing work-life balance and personal satisfaction. Background: Physicians are subject to high levels of mental, physical, and emotional stress, partly due to increasing administrative burdens. Online coaching is a proven intervention to help physicians improve workflow efficiency, reduce administrative burden and improve job satisfaction. Design: This voluntary longitudinal survey took place between 2020 and 2023. Physicians were asked to complete a survey at program entry and again 30-90 days after program completion. The survey consisted of 14 Likert scale questions, and a final sample of 280 physicians completed both surveys. Intervention: CCP contains modules that teach workflow improvements for clinical days, including timely charting, administrative task workflow, managing patient consultations and reducing interruptions. Interventions include self-paced modules, live coaching, recordings and an online peer community. Results: Post-CCP physicians reported a significant decrease in hours spent charting (P<0.0001) and completing clinical paperwork outside of clinical hours (P<0.006). Physicians also reported a decrease in work-related dread (P<0.001), feelings of burnout (P<0.001), and thoughts of quitting due to administrative burdens (P<0.001). Physicians felt more focused at work (P<0.001), felt more in control of the clinical day (P<0.001), and rated their mental energy at work higher (P<0.001). The program did not affect the number of patients seen in a full clinical day (P > 0.918). Conclusion and Relevance: The CCP reduces the time physicians spend on tasks outside of clinical hours, increasing free time without decreasing the number of patients seen per day.

Perioperative safety checklists standardize critical actions, but reliable completion depends on the surrounding work system and team behavior. We conducted a prospective observational analytic study from April to May 2026 in the central surgical unit of a high-volume public teaching referral hospital in Indonesia to examine whether patient safety culture and teamwork were associated with directly observed perioperative safety compliance and whether teamwork mediated the culture-compliance relationship. Patient safety culture was measured with the Hospital Survey on Patient Safety Culture 2.0, teamwork with a 35-item TeamSTEPPS Teamwork Perceptions Questionnaire research adaptation, and compliance by direct role-based observation using a 45-item checklist derived from the AORN Comprehensive Surgical Checklist. Eighty of 92 recruited professionals contributed 240 person-operation observations across 50 operations. Overall compliance was 74.75%, with sign-out lowest at 70.68%. Patient safety culture was associated with teamwork ({beta} = 0.590; 95% CI 0.510-0.770) and directly with compliance ({beta} = 0.407; 95% CI 0.187-0.712). The teamwork-compliance coefficient was positive ({beta} = 0.285; p = 0.046), but the prespecified percentile 95% CI included zero (-0.045 to 0.517). The indirect effect through teamwork was not supported ({beta} = 0.168; p = 0.079). These findings support a system-level interpretation of perioperative safety and identify learning-oriented responses to error, situation monitoring, and sign-out fidelity as measurable targets for future improvement efforts.

Indiana still faces significant health challenges, ranking among the least healthy U.S. states due to high obesity rates, mental health issues, and other chronic conditions. These disparities are closely linked to inequities in healthcare access, which are largely shaped by social determinants of health. Using data from the Social Vulnerability Index and County Health Rankings and Roadmaps, this study analyzes trends in obesity, mental health, and premature death across Indiana counties before, during, and after the COVID-19 pandemic. Descriptive statistics, correlation analyses, and Negative Binomial regression models were used to evaluate county-level disparities. In 2018, higher rates of uninsured, obese, and physically inactive populations were associated with increased premature death. In 2020, diabetes, smoking, and alcohol consumption were significant factors. By 2022, unemployment, education, obesity, insurance, exercise access, and mental health provider availability were associated with premature death. Findings indicate that socially vulnerable counties experienced amplified health impacts, with obesity rising most sharply where exercise infrastructure was limited and poor mental health days increasing across all counties. These results highlight persistent service gaps and the critical need for targeted investments in recreational infrastructure and mental healthcare. Future research should examine policy influences and causal relationships to inform equity-focused interventions.

Background Although often perceived as a technical tool, a data bank is fundamental for district performance management, facilitating integrated coordination, data consolidation, and routine information use for decision-making. However, implementation unfolds within hierarchical bureaucratic systems shaping authority distribution, workload allocation, coordination, and resource use. This study examines the political economy of institutionalizing a district-level health data bank in West Sumbawa District, Indonesia. Method A longitudinal qualitative case study was conducted in West Sumbawa District, West Nusa Tenggara Province, Indonesia, from November 2025 to March 2026 across three evaluation phases (baseline, midline, endline), involving 25 District Health Office (DHO) officers appointed to the Health Data Bank team, representing five organizational units, including the Secretariat, General and Human Resources Unit, and Public Health Division. Data were collected through participatory workshops, focus group discussions, in-depth interviews, observation, and document review, including official decrees, SOPs, meeting minutes, and implementation records, and analysed using Bossert's Decision Space Framework combined with a problem-driven political economy analysis examining how power relations, institutional norms, workload, resource support, and perceived incentives influenced whether technical reforms became operationalized in routine practice. Results The Health Data Bank progressed from strong institutional acceptance to structural formalization. Decision-making authority remained centralized within the Secretariat, enabling coordination but limiting distributed ownership. Resource constraints increased workload, concentrated in the Secretariat and division coordinators responsible for data consolidation and validation, without dedicated financing or staffing, despite improved analytical capacity. Accountability mechanisms were established through governance instruments, though enforcement and feedback loops remained underdeveloped. Data submission, validation, and use were not yet fully institutionalized, resulting in a gap between structural readiness and functional use. Conclusion Data institutionalization involves both technical and organizational processes, requiring collaborative negotiation of authority, workload, and resources. Continued attention to these factors will help structural formalization translate into sustainable operational outcomes.

Nineteen individuals with diverse public health leadership experience across different levels and domains, from countries with varying levels of economic development, and who have direct involvement in crises were interviewed. A concise literature review was conducted, examining the intersection of politics and public health leadership, as well as a brief review of relevant existing leadership courses, training programs, and fellowships. The interviews were transcribed in full, anonymized, coded (total 1104 coded excerpts, 762 discrete excerpts), and used as the basis for analyzing findings. Our research identified four thematic areas at the intersection of public health and political leadership in public health crises: attributes and skills; role of and threshold for political engagement; structural elements underpinning effective public health response; and modalities for building public health leadership. Public health leaders need to learn core skills, especially effective communication, diplomacy, and advocacy, and cultivate key attributes, especially integrity and humility, that support their ability to engage with political decision makers. Political leaders need to contribute productively ways, and at the appropriate time, to ensure societal cohesion and facilitate a well-resourced multisectoral response with public health at its core. Pre-established relationships and coordination mechanisms can play a supporting and productive role when crises strike. Strategies that incorporate experiential learning, peer collaboration, and mentorship are central to building the skills public health leaders need to succeed in crises. Many tangible steps can be taken to foster and support public health leadership including: integrating the political dimensions of public health into public health education; tailoring public health trainings to include practical skills such as stakeholder engagement, effective communication, negotiation, policy advocacy, and community engagement; creating supportive ecosystems through peer, mentor, and fellowship approaches; and advocating for strengthening the structural interface between politics and public health.

Background Innovation in pharmaceutical sectors operating under resource and institutional constraints may depend not only on knowledge and attitudes but also on the conditions that enable innovation-related activities to occur. This study examined the relationships among intellectual property (IP) literacy, innovation attitudes, innovation readiness, and reported innovation practice among pharmaceutical professionals in Syria. Methods A cross-sectional survey was conducted among 303 pharmaceutical professionals between March and April 2026. Four composite indices were constructed to assess IP literacy, innovation attitudes, innovation readiness, and innovation practice. Descriptive statistics, correlation analyses, group comparisons, and multivariable regression models were used to characterize patterns of association among study domains. The analysis was designed to identify empirical patterns rather than infer causal relationships. Results Innovation attitudes were comparatively high (73.56/100), whereas innovation readiness (17.00/100) and innovation practice (12.65/100) were substantially lower. IP literacy was positively associated with innovation readiness (r = 0.384, p < 0.001) and innovation practice (r = 0.205, p < 0.001). In contrast, innovation attitudes were not significantly associated with reported innovation practice (p = 0.332). Regression analyses indicated that the inclusion of innovation readiness improved model fit beyond specifications based on knowledge and attitudes alone ({Delta}R{superscript 2} = 0.058, p = 0.028). Significant differences in readiness and practice were observed across professional groups (p < 0.001), whereas knowledge and attitudes showed limited variation. Conclusions High levels of innovation-related knowledge and positive attitudes did not correspond to high levels of reported innovation practice in this setting. The findings suggest that innovation readiness may capture enabling conditions that are not reflected by knowledge or attitudinal measures alone. These results support the value of examining contextual and institutional factors when assessing innovation capacity in resource-constrained pharmaceutical systems. Given the substantial gap observed between innovation attitudes and innovation practice, educational strategies may represent one avenue for strengthening innovation readiness. In the Syrian context, strengthening innovation-oriented education and university-industry engagement may help cultivate innovation competencies and support the translation of research into practical applications.

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: Whether corrective actions documented in medical safety incident reports rely on individual vigilance ("Safety-I") or on structural, system-level intervention ("Safety-II") has not been quantitatively evaluated on a national scale in Japan. We developed an automated classification pipeline to assign corrective-action free-text to a 7-level maturity scale (L0-L6) and computed two summary indices: the Safety Measure Quality Profile (SMQP), the full L0-L6 distribution, and the System-based Safety Measure Rate (SSMR), the proportion of non-L0 records classified L3-L6. Methods: We analyzed all 11,507 corrective-action free-text entries from the 2010 release of Japan's national medical accident and near-miss reporting database (Japan Council for Quality Health Care, JCQHC), comprising 8,804 near-miss (Hiyari-Hatto) and 2,703 accident (Jiko) reports. Records were classified using a five-stage hybrid pipeline: an expert-developed rule dictionary, TF-IDF + k-nearest-neighbor matching, cosine-similarity matching, a two-tier large-language-model (LLM) classifier, and a conservative priority-cascade fallback. SSMR was compared between near-miss and accident reports using a chi-square test, Wilson 95% confidence intervals, Cramer's V, and the risk difference (RD), against pre-specified minimal clinically important difference (MCID) criteria of RD >= 2 percentage points and Cramer's V >= 0.10. Results: Every record received a definitive L0-L6 label (0% unresolved). Overall, 16.6% of records were unclassifiable (L0); among the 9,599 classifiable (non-L0) records, individual-vigilance actions (L1) predominated (54.6% of all records), and only 11.82% (95% CI, 11.19-12.49%) met the SSMR criterion (L3-L6). SSMR was higher for accident reports than for near-miss reports (18.12% [95% CI, 16.69-19.64%] vs. 9.[95% CI,46% [95% CI, 8.80-10.17%]; RD = 8.66 percentage points; Cramer's V = 0.120; chi-square(1) = 136.97001), exceeding both pre-specified MCID thresholds. Conclusions: In this interim single-year analysis, the large majority of documented corrective actions in Japanese medical safety reports remained individual-vigilance-based rather than system-based, with accident reports showing a substantively, rather than merely statistically, higher proportion of system-based actions than near-miss reports. These findings support the feasibility of large-scale automated assessment of corrective-action quality and provide the rationale for the planned 16-year longitudinal analysis.

Cancer prevalence is distributed unevenly across regions and caused by the interaction of multiple risk factors. Previous studies focused on the use of global modeling techniques to predict cancer at the county level that overlooks important spatial differences. This study aims to develop geographically weighted machine learning models to predict cancer prevalence at the census tract level in the United States and identify local determinants of cancer burden. First, a scoping review was conducted to find a list of measurable drivers of cancer in the United States. Using this list, the data of these variables for 84415 census tracts were obtained from the Center for Disease Control and Prevention PLACES dataset and other publicly accessible resources. Then, several predictive models, including Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR), as well as Random Forest, XGBoost, and Deep Neural Network and their geographically weighted counterparts, were developed and compared using the Coefficient of Determination, Root Mean Square Error, and Absolute Error. Results presented that geographically weighted models outperformed other methods, and geographically weighted XGBoost achieved the strongest and most consistent overall performance with pseudo-R2 ranging between 0.89 and 0.98. Feature importance analysis of this model illustrated that most important cancer drivers changed location by location. Aged people, racial composition, preventative behaviors, and metabolic conditions such as diabetes, hypertension, and high cholesterol were determined as influential predictors, although their relative importance varied across regions. These findings revealed the value of localized models at a small geographic scale to identify regional cancer risk patterns and help the allocation of proper resources to hotspot areas. Keywords: Cancer prevalence, Census tracts, geographically weighted machine learning models, Deep neural network, XGBoost, Random Forest, Ordinary Least Squares, risk factor, determinant

Background Floods are among the most devastating natural disasters worldwide and are increasingly associated with adverse mental health outcomes, particularly Post-Traumatic Stress Disorder (PTSD). In December 2023, Hanang District in northern Tanzania experienced catastrophic mud floods that resulted in extensive loss of life, destruction of property, displacement of households, and disruption of livelihoods. While emergency humanitarian responses focused primarily on physical needs, limited evidence exists regarding the long-term psychological consequences among survivors. Therefore, this study aimed to determine the patterns of PTSD manifestations and assess cognitive factors associated with PTSD symptoms among flood victims in Hanang District, Tanzania. Methods A community-based cross-sectional study was conducted among 360 flood victims one year after the disaster. PTSD symptoms were assessed using the PTSD Checklist for DSM-5 (PCL-5). Descriptive statistics summarized PTSD severity, while chi-square tests and regression analyses examined associations between socio-demographic characteristics and PTSD manifestations. Cognitive factors were assessed based on participants' exposure to traumatic experiences and perceptions of traumatic events. Results The mean PCL-5 score was 39.2 (SD = 20.6), indicating a high burden of psychological distress. Approximately 45% of respondents had severe PTSD symptoms (PCL-5 [&ge;]45), while another substantial proportion demonstrated moderate symptom severity. PTSD manifestations varied significantly by geographical location (p < 0.001), household income (p = 0.011), and marital status (p = 0.002). Age positively predicted PTSD severity ({beta} = 0.019, p = 0.001), whereas household income negatively predicted symptom severity ({beta} = -0.297, p = 0.001). Exposure to natural disasters constituted the predominant cognitive factor, with 45% directly experiencing the flood and 38.3% witnessing the event. Exposure to secondary traumatic experiences through witnessing or learning about violent events was also common. Cognitive trauma exposure demonstrated a significant association with PTSD symptoms ({chi}2, p < 0.001). Conclusion PTSD remains highly prevalent among flood survivors in Hanang district. Both direct and indirect trauma exposure significantly contributed to PTSD manifestations. Comprehensive disaster recovery programmes should integrate trauma-focused psychological services, cognitive behavioural interventions, routine PTSD screening, and community-based psychosocial support alongside socioeconomic recovery initiatives.

Objectives: To describe age-group differences in inability to afford dental treatment and cost related dental delay, among the US community-dwelling population. Study design: Descriptive analysis of nationally representative survey data. Methods: Using nationally representative Medical Expenditure Panel Survey data (2018-2021), we examined trends in inability to afford dental treatment and cost-related dental treatment delays across four age groups (2-17, 18-39, 40-64, [&ge;]65 years). Weighted analyses accounted for the complex survey design; statistical significance was set at p<0.001. Results: Cost-related delays declined modestly from 2018 to 2021 but remained most prevalent among adults aged 40-64 (4.8% for ages 40-64, 3.4% for ages 18- 64, 2.2% for ages>65 in 2021; p<0.001). Conclusion: Middle-aged adults seem to experience delays due to cost, underscoring the need for dental coverage to expand dental coverage for this group and to reduce their out-of-pocket costs.

Introduction: Engaging Community Influencers (CIs) was a key strategy for polio eradication in India, also contributing to routine vaccination and COVID-19 vaccination. CIs were high status individuals selected for their pre-existing reach into vaccine-hesitant communities. This paper describes the factors that kept the CIs engaged over time. The findings add to our understanding of what drives CHW motivation. Methods: We performed a thematic analysis of 65 in-depth interviews conducted across six study districts of Uttar Pradesh, involving 36 CIs, 18 CGPP field staff, nine project managers and two representatives from other stakeholders. Findings: The most important motivational factors that emerged from the research were improved social status, altruism, and effective working relationships. The inputs required to foster these were information support; providing respect and visibility; and fostering robust working relationships between program staff, CIs, CHWs, and government functionaries. Conclusions: CIs' engagement in the program maintained and bolstered their pre-existing status. Deploying and sustaining this cadre requires a strategic approach to maintaining motivation over time. Providing respect and visibility and maintaining effective working relationships is key to sustaining the CIs' motivation.

Aims: To assess whether recent declines in U.S. rolling 12-month-ending drug overdose death counts are projected to continue, compare the retrospective performance of short-term forecasting models, and estimate national and regional 12-month changes. Design: Comparative time-series forecasting study with a retrospective March 2025-February 2026 forecast evaluation and subsequent 12-month-ahead projections through February 2027. Setting: United States and four U.S. Census regions: Northeast, Midwest, South, and West. Cases: Aggregate drug overdose deaths reported in the National Center for Health Statistics Vital Statistics Rapid Release system (VSRR) and identified using ICD-10 underlying cause-of-death codes X40-X44, X60-X64, X85, and Y10-Y14. Measurements: The primary outcome was the monthly series of rolling 12-month-ending overdose deaths. Candidate models included ARIMA, generalized additive models, Prophet, and AICc-ranked n-sub-epidemic models. Models were calibrated using January 2020-February 2025 data and evaluated against March 2025-February 2026 observations using mean absolute error, mean squared error, empirical 95% prediction interval coverage, and weighted interval score (WIS). Individual models were ranked by retrospective WIS, and normalized inverse-WIS weights were used to construct ensembles from the top-ranked models. Final forecasts were generated for March 2026-February 2027 after recalibrating models using January 2020-February 2026 data. Results: Retrospective WIS performance differed geographically: GAM performed best nationally and in the Midwest and West, the leading n-sub-epidemic model in the Northeast, and ARIMA in the South. Median forecasts from all individual models and ensembles projected declines from February 2026 to February 2027 nationally and in each region, although prediction intervals varied substantially. Individual national median projections ranged from declines of 12.8% to 25.8%, while weighted-ensemble median projections indicated declines of 20.5% to 21.7%. Projected weighted-ensemble declines were larger in the Northeast (25.4%-30.0%) and Midwest (24.3%-26.3%) than in the South (16.6%-19.5%) and West (18.0%-21.8%). Summary: Ensemble forecasts of the reported provisional VSRR series were consistent with continued declines in rolling annual overdose death counts nationally and across U.S. Census regions. The projected magnitude of decline differed by region and model specification. Because the forecasts used provisional rolling 12-month-ending counts, they should be interpreted as surveillance projections rather than exact monthly mortality predictions.

Background Deconfliction is a central pillar of humanitarian risk mitigation in contemporary armed conflicts. Intended as a notification system through which parties to a conflict can mitigate against harm to humanitarian personnel and infrastructure, its effectiveness is dependent on respect for humanitarian protections. Since October 2023, repeated Israeli attacks on deconflicted sites and routes in Gaza, alongside increasing restrictions on humanitarian movement as notification-based coordination was replaced by a permission-based system, have raised fundamental questions about the utility and function of deconfliction. This study examines how deconfliction shaped humanitarian access, healthcare delivery, and Palestinian health infrastructure from the perspective of international healthcare workers in Gaza since 2023. Methods We conducted semi-structured interviews with 18 international healthcare providers who worked in Gaza between January 2024 and December 2025. Participants completed 31 deployments across 16 healthcare facilities. Interviews were analyzed using inductive thematic analysis. Results Two major themes emerged. First, participants described deconfliction as an unstable and ineffective means of ensuring humanitarian protection or access. They reported delays, denials, sudden revocations of movement permissions, and strikes on deconflicted sites. These conditions disrupted clinical care, delayed transfers and evacuations, limited facility access, and exposed both patients and providers to ongoing risk. Second, participants described deconfliction as a mechanism of control that shifted responsibility for protection from parties to a conflict to humanitarian actors and redirected resources and personnel away from Palestinian hospitals toward NGO (Non-Governmental Organization) facilities, eroding Palestinian healthcare autonomy. Conclusion Rather than a neutral protection mechanism, deconfliction operated as a conditional authorization regime through which Israel regulated humanitarian movement, medical supply chains, and healthcare delivery. This mechanism rendered protection contingent on compliance, allowing Israel to reframe attacks as humanitarian operational failures rather than violations of international law by military actors. Deconfliction also facilitated the substitution of Palestinian healthcare with internationally managed structures that were dependent on Israeli approval. By undermining local health system autonomy, deconfliction was instrumentalized within a broader Israeli strategy to deliberately inflict conditions to bring about the physical destruction of life in Gaza. These findings raise urgent questions about humanitarian actors obligations when operating within non-neutral systems and underscore the need to prioritize direct support for local healthcare institutions.

Background: Stress research in nursing education has largely focused on distress, stressors, and negative outcomes, although challenging experiences may also support motivation, confidence, learning, and growth when appraised positively. Objective: To develop and evaluate the psychometric properties of the Nursing Student Positive Stress Scale (NSPSS). Design: A methodological instrument development and psychometric evaluation study. Methods: The NSPSS was developed using a deductive, theory-driven approach informed by the transactional theory of stress and coping and positive psychology perspectives. Content validity was assessed by an international nursing expert panel. Psychometric evaluation used national survey data from nursing students in New Zealand. Of 539 responses, 507 were analysed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted using separate subsamples. Internal consistency was assessed using Cronbach's alpha and McDonald's omega, and convergent validity through correlation with Perceived Stress Scale-10 scores. Results: Content validity was strong (I-CVI = .88-1.00; S-CVI/Ave = .975; S-CVI/UA = .800). EFA identified a dominant factor explaining 41.38% of variance (loadings = .528-.735). CFA supported a two-context Academic and Clinical Positive Stress model with correlated residuals between five parallel item pairs, chi-square(29) = 60.49, CFI = .970, TLI = .954, RMSEA = .063, SRMR = .065. Internal consistency was good (alpha = .839; omega = .843). NSPSS scores correlated negatively with PSS-10 scores (r = -.298, p < .001). Conclusion: The NSPSS demonstrated strong content validity, preliminary evidence of structural and convergent validity, and good internal consistency reliability for assessing positive stress appraisal among nursing students. Further validation in independent samples is warranted.

Against the backdrop of nationwide inclusive education promotion, children with autism spectrum disorder, intellectual disabilities and other special educational needs (SEN) in Jiangxi Province have raised growing demands for equitable schooling. Paraeducators serve as a critical on-site support mechanism enabling SEN children to access mainstream classrooms; the adequacy of shadow teacher service provision and the maturity of corresponding multi-stakeholder support systems jointly determine the overall quality of local inclusive education. This study adopted mixed quantitative-qualified methods, including questionnaire surveys and semi-structured interviews, to investigate SEN children, paraeducators, general and special education teachers, as well as SEN caregivers across multiple prefecture-level cities in Jiangxi. Grounded in provincial special education policies and local frontline inclusive education practices, we systematically unpacked multidimensional service demands from four core stakeholder groups, diagnosed prominent practical bottlenecks restricting the sustainable operation of shadow teacher services, and constructed regionally tailored multi-layered support strategies aligned with Jiangxi's educational realities. The findings of this research offer empirical evidence and actionable policy references to advance high-quality inclusive education for SEN children across central China's Jiangxi Province.