Search Results (1,473)

This study aims to understand the meaning nursing professionals attribute to their lived experiences of providing humanized care within a public hospital setting. Grounded in Jean Watson’s theory of human caring, the research adopts a qualitative, descriptive phenomenological design to capture the perceptions and emotions of nurses regarding humanized care. Data were collected through semi-structured interviews with nine experienced nurses, selected through purposive sampling. The interviews, conducted virtually between July and December 2024, were analyzed using Colaizzi’s method and supported by Atlas.ti software. Four main thematic categories emerged: institutional health policies, professional image and identity, strengths and challenges in care, and essential competencies for humanized care. The findings highlight the critical role of empathy, cultural sensitivity, ethical commitment, and emotional presence in delivering compassionate care. Participants emphasized that, beyond clinical procedures, humanized care requires relational and contextual sensitivity, often hindered by institutional limitations and excessive administrative burdens. The study concludes that nursing professionals are key agents in promoting ethical, empathetic, and culturally respectful practices that humanize health services. These insights offer valuable contributions for designing policies and training strategies aimed at strengthening humanized care as a cornerstone of quality healthcare systems. Full article

Background: Access to safe and reliable water and sanitation remains a critical public health and development challenge, with rural and low-income communities being disproportionately affected by inadequate services and heightened exposure to waterborne diseases. Despite global efforts and infrastructure-based progress indicators, significant disparities persist, and these often overlook users’ perceptions of water quality, reliability, and safety. This study explores the determinants of household satisfaction with drinking water in rural areas, comparing subjective user feedback with official access data to reveal gaps in current monitoring approaches and support more equitable, user-centered water governance. Methods: This study was conducted in Kazakhstan’s Atyrau Region, where 1361 residents from 86 rural villages participated in a structured survey assessing household access to drinking water and perceptions of its quality. Data were analyzed using descriptive statistics and multinomial logistic regression to identify key predictors of user satisfaction, with results compared against official records to evaluate discrepancies between reported experiences and administrative data. Results: The field survey results revealed substantial discrepancies between official statistics and residents’ reports, with only 58.1% of respondents having in-house tap water access despite claims of universal coverage. Multinomial logistic regression analysis identified key predictors of user satisfaction, showing that uninterrupted supply and the absence of complaints about turbidity, odor, or taste significantly increased the likelihood of higher satisfaction levels with drinking water quality. Conclusions: This study underscores the critical need to align official water access statistics with household-level experiences, revealing that user satisfaction—strongly influenced by supply reliability and sensory water quality—is essential for achieving equitable and effective rural water governance. Full article

Despite growing global momentum to reduce the number of children who never received a dose of any vaccine, i.e., zero-dose (ZD) children, persistent geographic and social inequities continue to undermine progress toward universal immunization coverage. In Madagascar, where routine vaccination coverage remains below 50% in most regions, the non-governmental organization Doctors for Madagascar and public sector partners are implementing the SOAMEVA program: a targeted community-based initiative to identify and reach ZD children in sixteen underserved districts in the country’s south. This paper outlines the equity-sensitive evaluation design developed to assess the implementation and impact of SOAMEVA. It presents a forward-looking evaluation framework that integrates both quantitative program monitoring and qualitative community insights. By focusing at the fokontany level—the smallest administrative unit in Madagascar—the evaluation captures small-scale variation in ZD prevalence and program reach, allowing for a detailed analysis of disparities often masked in aggregated data. Importantly, the evaluation includes structured feedback loops with community health workers and caregivers, surfacing local knowledge on barriers to immunization access and program adoption. It also tracks real-time adaptations to implementation strategy across diverse contexts, offering insight into how routine immunization programs can be made more responsive, sustainable, and equitable. We propose eight design principles for conducting equity-sensitive evaluation of immunization programs in similar fragile settings. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

Chainsaws are widely used in various occupational settings, including forestry, landscaping, farming, and by homeowners for tasks like tree felling, brush clearing, and firewood cutting. However, the use of chainsaws poses significant risks to operators and bystanders. This research quantified and compared occupational and nonoccupational injuries caused by contact with chainsaws and related objects during the period from 2018 to 2022. The emergency department and OSHA (Occupational Safety and Health Administration) data were used to characterize the cause and nature of the injuries. Results suggest that for this five-year period an estimated 127,944 people were treated in U.S. emergency departments for chainsaw-related injuries. More than 200 non-fatal and 57 fatal occupational chainsaw-involved injuries were found during the same period. Landscaping and forestry were the two industries where most of the occupational victims were employed. Upper and lower extremities were the most likely injured body parts, with open wounds from cuts being the most common injury type. The majority of fatal injuries were caused by falling objects such as trees and tree limbs while using a chainsaw. Our suggestions to reduce injuries include proper training and wearing personal protective equipment, as well as making sure any bystanders are kept in a safety zone away from trees being cut. Full article

Background and Aim: Type 2 diabetes (T2D) continues to pose a significant public health challenge worldwide. Among therapeutic options, glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have proven effective in optimizing glycemic control and improving cardiometabolic profiles. Semaglutide, now available in an oral formulation, represents a modern strategy to improve patient adherence while supporting glucose and weight regulation. This study primarily investigated the effects of oral semaglutide on key metabolic indicators and secondary endpoints included cardiovascular risk markers (blood pressure and lipid profile) and patient-reported quality of life (QoL). Study Design and Methods: A longitudinal, prospective observational study was conducted involving patients with T2D across two Italian healthcare facilities. Participants were assessed at baseline (T0) and at three subsequent intervals—6 months (T1), 12 months (T2), and 18 months (T3)—following the initiation of oral semaglutide use. Key Findings: Out of 116 participants enrolled, 97 had complete and analyzable data. Across the 18-month follow-up, significant improvements were observed in glycemic parameters, with a notable reduction in HbA1c levels (T0 vs. T3, p = 0.0028; p ≤ 0.05, statistically significant). Self-reported outcomes showed enhanced quality of life, especially in treatment satisfaction and perceived flexibility (T0 vs. T3, p < 0.001). Conclusions: Daily administration of 14 mg oral semaglutide in individuals with T2D resulted in substantial benefits in glycemic regulation, weight reduction, cardiovascular risk management, and overall patient satisfaction. These findings reinforce its potential role as a sustainable and effective option in long-term diabetes care from both a clinical and public health perspective. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

This study analyses the conditions under which co-opetition improves the supply of healthcare services in Benin. Using non-centralised administrative data from a sample of public and private health centres, we apply network theory and negative binomial regression to assess the extent to which competition affects collaboration between public and private healthcare providers. We found that competition reduces the degree of collaboration between private and public health providers. However, the COVID-19 pandemic significantly mitigated this effect, highlighting the potential for competition within the healthcare system without compromising social welfare. Notwithstanding that, we show that these benefits are not sustained over time. These findings have policy implications for the sustainability of health system financing in Africa, particularly by promoting sustainable financial mechanisms for the private sector and more inclusive governance structures. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

Background/Objectives: The Rapid Access and Stabilization Program (RASP), launched in Nova Scotia in April 2023, aims to improve timely psychiatric care, reduce reliance on emergency services, and provide early intervention. This study describes the sociodemographic and clinical characteristics of the RASP participants and examines their association with acute service use. Methods: This cross-sectional descriptive study used self-reported surveys and administrative data from 738 RASP participants. Descriptive statistics summarized key sociodemographic and clinical variables. Associations between these characteristics and acute service use (emergency department visits, inpatient admissions, and mobile crisis calls) were examined using chi-square and Fisher’s Exact tests. Bonferroni correction was applied for multiple comparisons. Results: The sample was predominantly female (65.2%) and aged 20–40 years (38.4%). Despite high rates of severe anxiety (53.9%) and depression (36.0%), acute service use was low: emergency department visits (7.2%), mobile crisis calls (1.0%), and inpatient admissions (0.8%). Preliminary analyses showed that education level and housing status were associated with ED visits and inpatient admissions. However, these associations did not remain statistically significant after Bonferroni correction. Conclusions: Although mental health symptom severity was high, acute mental health service use remained low after RASP enrollment, indicating the program’s potential in reducing reliance on crisis services. No participant characteristics were significantly associated with acute service use after adjustment, underscoring the complexity of predicting utilization and the need for robust multivariable models. Continued investment in rapid access programs may be essential to improving timely mental health care and supporting early intervention strategies. Full article

Localised cutaneous leishmaniasis (LCL) is a common neglected tropical disease in Ethiopia, which is mainly treated with intralesional (IL) pentavalent antimonial such as sodium stibogluconate (SSG) and/or cryotherapy. Both treatments are painful, and studies are lacking on the pain associated with these or affected individuals’ experiences of them. A cross-sectional, observational study was conducted at ALERT Comprehensive Specialized Hospital, Addis Ababa/Ethiopia. The socio-demographic and clinical data of individuals affected by LCL receiving IL SSG and/or cryotherapy was gathered, and their treatment was observed. Participants quantified their treatment-associated pain using the Wong–Baker Pain Scale. Health-related quality of life was measured using the (Children’s) Dermatology Life Quality Index. Adverse effects, participant experiences with local therapies, and dermatologists’ experiences and opinions of local LCL treatment were assessed using structured questionnaires. Of the thirty-six individuals with LCL included (64% male, 14% children), 52% reported a treatment-associated pain score ≥ 8. Cryotherapy administered with a cotton bud was associated with lower pain scores ≤ 6 (odds ratio: 0.15, 95% confidence interval: 0.03–0.89) compared to a cryotherapy spray device. There was wide variation in treatment administration. Local LCL treatment is painful, and most individuals experience significant pain. This study highlights the need for less painful but effective treatments, structured training, and clear standard operating procedures. Full article

Geographic disparities threaten equitable access for children to health-promoting safe green spaces, and quality early education in the communities in which they live and grow. To address gaps in the field, we integrated the fields of developmental psychology, public health, and environmental science to examine, at the population level, associations between the environmental burden, socioeconomic vulnerability, and kindergarten readiness in a diverse urban county. Three administrative datasets were integrated through an early childhood data sharing research partnership in Miami-Dade County. The Bruner Child Raising Vulnerability Index, the five domains of the Environmental Burden module from the Environmental Justice Index, and public school kindergarten readiness scores were aggregated at the census tract level. Analysis of variance and multiple regression analyses found associations between socioeconomic vulnerability and race/ethnicity. The socioeconomic vulnerability levels were highest in census tracts with a higher percentage of Black residents, compared to all other races/ethnicities. Areas of greater social vulnerability had lower kindergarten readiness and a higher environmental burden. A higher environmental burden predicted lower kindergarten readiness scores above and beyond race/ethnicity and socioeconomic vulnerability. The findings advance our understanding of global challenges to sustainable healthy child development, such as the persistence of a disproportionate environmental burden and inequitable access to resources such as green spaces and early education programs. The present study results can inform community health improvement plans to reduce risk exposures and promote greater access to positive environmental and educational resources for all children. Full article

Objective: Pulmonary arterial hypertension (PAH) is a progressive and life-threatening disease. Adverse events (AEs) related to its drug treatment seriously damaged the patient’s health. This study aims to clarify the causal relationship between PAH drugs and these AEs by combining pharmacovigilance signal detection with the Bayesian causal network model. Methods: Patient data were obtained from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), covering reports from 2013 to 2023. In accordance with standard pharmacovigilance methodologies, disproportionality analysis was performed to detect signals. Target drugs were selected based on the following criteria: number of reports (a) ≥ 3, proportional reporting ratio (PRR) ≥ 2, and chi-square (χ²) ≥ 4. Bayesian causal network models were then constructed to estimate causal relationships. The do-calculus and adjustment formula were applied to calculate the causal effects between drugs and AEs. Results: Signal detection revealed that Ambrisentan, Bosentan, and Iloprost were associated with serious AEs, including death, dyspnea, pneumonia, and edema. For Ambrisentan, the top-ranked adverse drug events (ADEs) based on average causal effect (ACE) were peripheral swelling (ACE = 0.032) and anemia (ACE = 0.021). For Iloprost, the most prominent ADE was hyperthyroidism (ACE = 0.048). Conclusions: This study quantifies causal drug–event relationships in PAH using Bayesian causal networks. The findings offer valuable evidence regarding the clinical safety of PAH medications, thereby improving patient health outcomes. Full article

Background/objectives: In 9/2020, the United States Food and Drug Administration )FDA( posted a black box warning for all benzodiazepines, addressing their association with serious risks of abuse, addiction, physical dependence, and withdrawal reactions. We evaluated changes in benzodiazepine dispensing rate trends after this warning. Methods: The dataset of Clalit Health Services (Israel’s largest insurer, with 5 million members) was used to identify and collect benzodiazepine dispensing data for all patients who were dispensed these drugs at least once during the study period (1/2017–12/2021). The dispensing rate (number of patients who were dispensed benzodiazepines per month divided by the number of patients alive during that month) was calculated for each month in the study period. Linear regression and change point regression were used to review the change in trend before and after the black box warning. New users of benzodiazepines after the black box warning were analyzed by age. Results: A total of 639,515 patients using benzodiazepines were reviewed. The mean benzodiazepine dispensing rate per month was 0.21 and ranged from 0.17 (in 2/2017) to 0.24 (in 3/2020). No significant change in trend was observed before vs. after the black box warning (slopes of 0.00675 percentage points per month and 0.00001 percentage points per month, respectively; p = 0.38). The change point regression analysis identified a change point in 4/2019, which is prior to the black box warning. New users were younger after the black box warning compared to before this warning. Conclusions: The FDA black box warning did not affect the dispensing rate of benzodiazepines. Full article