Preventive Measures Research Articles

Factors that Increase the Risk of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic disorder of the gastrointestinal tract. It comprises Crohn’s disease (CD) and ulcerative colitis (UC) The disorder begins in young adulthood. It is characterised by remission and relapse. IBD significantly affects a person’s life more so, their productivity and ability to perform activities of daily living. Although IBD is prevalent in Western countries, the recent epidemiology data shows a rising global prevalence and incidence. Addressing IBD is important. Although it is not significantly associated with high morbidity rates, it is a significant burden to healthcare. Identifying the risk factors of IBD can help in improving preventative measures. Since IBD does not have a known cure, controlling for these factors can minimize the impact of the disease. Some of the risk factors that increase the risk of IBD are genetics, environmental factors such as smoking, diet, lifestyle changes, medications, and intestinal microbiome. Identifying the factors that contribute to the risk of developing IBD can help in creating effective measures that can prevent the pathogenesis of the disease.

중대재해처벌 등에 관한 법률 시행에 따른 사회복지조직의 대응방안

The Serious Accidents Punishment Act was expanded to apply to all workplaces with five or more employees on January 27, 2024. This paper examines the major legal issues surrounding senior employment support agencies, especially senior clubs, which are social welfare facilities particularly vulnerable to major accidents, and proposes organizational countermeasures for preventing major accidents. To this end, this paper analyses the main contents of the Serious Accidents Punishment Act through academic literatures, and reviews various legal principles and key issues related to the implementation of the Act on senior clubs through the case laws. This paper aims to seek effective preventive measures and responses to the accidents that occur in senior clubs. The research revealed that the characteristics of senior clubs include continuous increasing trend in the number of elderly participants in senior job programs, full-time employments more than three hundred employees, various types of business operations such as public service, social service, and private business, and continuous occurrence of dangerous accidents. The key issues of the Serious Accidents Punishment Act relevant to the senior clubs are identifying an employee with legal responsibility, types of business subject to the Act, establishment of a dedicated occupational health and safety board appropriate to the type of business, a joint penal provision, and punitive damages. This paper proposes the following responsive measures for senior clubs in response to the implementation of the Act; changing employees’ perspective towards the Serious Accidents Punishment Act, building a health and safety management system reflecting characteristics of senior clubs, utilizing scientific risk management techniques in establishing a health and safety management system and support and management from the Ministry of Health and Welfare as well as local governments.

Integrative Interventions for Improving Outcomes in Depression: A Narrative Review

Antidepressants are among the most used medications in the US, with significant deleterious effects on people’s well-being. At any given time, depression impacts approximately 1 in 10 Americans, causing wide and broad societal costs. Interest is developing for non-pharmacological treatments and preventative measures. We summarize the literature on non-invasive dietary and lifestyle approaches for treating depression. This review aims to inform future research and treatment programs for depression by providing an evidentiary summary of integrative therapeutic approaches for depression.

Fear of Happiness with Relation to Mental Health with It's Preventive Measure

This research study examines the complicated phenomena of fear of happiness, including its social implications, psychological bases, and preventive measures. Fear of happiness has a substantial negative influence on one's general well-being, interpersonal relationships, and level of life satisfaction. It is frequently caused by subconscious beliefs or past experiences. This paper explores how fear of happiness appears in different situations and why it is detrimental to mental health, leading to self-destructive behaviors, heightened anxiety, and depression. It does this by using psychological theories and empirical research. Furthermore, the paper discusses preventive measures and interventions aimed at addressing the fear of happiness. They consist of mindfulness exercises, cognitive-behavioral methods, and positive psychology therapies that aim to eliminate unfavorable notions, foster self-compassion, and strengthen resilience.

The role of SLC26A4 in bony labyrinth development and otoconial mineralization in mouse models.

Inner ear malformations are predominantly attributed to developmental arrest during the embryonic stage of membranous labyrinth development. Due to the inherent difficulty in clinically assessing the status of the membranous labyrinth, these malformations are diagnosed with radiographic imaging, based on the morphological characteristics of the bony labyrinth. While extensive research has elucidated the intricacies of membranous labyrinth development in mouse models, comprehensive investigations into the developmental trajectory of the bony labyrinth, especially about its calcification process, have been notably lacking. One of the most prominent types of inner ear malformations is known as incomplete partition (IP), characterized by nearly normal external cochlear appearance but pronounced irregularities in the morphology of the modiolus and inter-scalar septa. IP type II (IP-II), also known as Mondini dysplasia, is generally accompanied by an enlargement of the vestibular aqueduct and is primarily attributed to mutations in the SLC26A4 gene. In the case of IP-II, the modiolus and inter-scalar septa of the cochlear apex are underdeveloped or missing, resulting in the manifestation of a cystic structure on radiographic imaging. In this overview, we not only explore the normal development of the bony labyrinth in mice but also present our observations on otolith mineralization. Furthermore, we investigated the specifics of bony labyrinth and otolith mineralization in Slc26a4-deficient mice, which served as an animal model for IP-II. We ensured that these findings promise to provide valuable insights for the establishment of therapeutic interventions, optimal timing, targeted sites, and preventive measures when considering the management of this condition.

IMAGE CLASSIFICATION OF VINE LEAF DISEASES USING COMPLEX-VALUED NEURAL NETWORK

Leaf diseases are a serious challenge in the agricultural industry affecting crop quality and yield especially in grapevines. Early recognition and classification of grape leaf diseases is crucial to enable farmers to take appropriate preventive measures in maintaining the health of their crops. The research utilized an innovative approach based on Complex-Valued Neural Network (CVNN) to address the problem. Using Complex-Valued Neural Network (CVNN) this research seeks to identify and classify grape leaf diseases through a series of experiments. A total of 100 images divided into 4 classes namely Black Rot, ESCA, Leaf Blight, and Healthy were collected to train the model. The results show that the trained CVNN model successfully achieved a training accuracy of 100% and a testing accuracy of 97%, demonstrating excellent performance in classifying grape leaf diseases. This states that the proposed approach has great potential to be an effective tool in helping growers manage their vineyards more efficiently and effectively. The developed image processing method is expected to be applied in designing a system to perform image classification of diseases on grape leaves.

Prevalence of Bronchial Asthma in Children in Southern Kyrgyzstan

Background: The aim of this study was to investigate the prevalence of bronchial asthma and other allergic diseases such as allergic rhinitis and atopic dermatitis among 6075 school-aged children in Osh, Jalal-Abad and Batken regions of Kyrgyzstan. Methods: 6075 children were questioned using the ISAAC questionnaire. Bronchial asthma symptoms are frequent – 21.1% of children had difficulty wheezing, and 13.4% had night cough. This indicates a high prevalence of bronchial asthma among children in the study population. The obtained morbidity rates significantly exceed the official statistics for the region. This indicates insufficient diagnosis of allergic diseases in children and substantiates the need to develop a set of measures aimed at optimizing the detection of cases of allergic pathology and increasing the effectiveness of therapeutic and preventive measures. Results: The results of the study demonstrate a high need for the development and implementation of a regional program for the diagnosis, treatment, and prevention of allergic diseases in children of Osh, Jalal-Abad, and Batken regions. Conclusion: Implementing such a program will contribute to better control of bronchial asthma and other allergic pathologies and improve the quality of life of the child population in the region.

Wearable Sensors and the Evaluation of Physiological Performance in Elite Field Hockey Players

Sports performance tracking has gained a lot of interest and widespread use in recent years, especially in elite and sub-elite sports. This makes it possible to improve the effectiveness of training, to calibrate and balance workloads according to real energy expenditure, and to reduce the likelihood of injuries due to excessive physical stress. In this context, the aim of this review was to map the scientific literature on wearable devices used in field hockey, evaluating their characteristics and the available evidence on their validity in measuring physiological and movement parameters. A systematic investigation was carried out by employing five electronic databases and search terms that incorporated field hockey, wearables, and performance analysis. Two independent reviewers conducted assessments of the 3401 titles and abstracts for inclusion, and at the end of the screening process, 102 full texts were analyzed. Lastly, a total of 23 research articles that specifically concentrated on field hockey were incorporated. The selected papers dealt with performance monitoring (6 papers), technical analysis and strategy game (6), injury prevention (1), and physiological measurements (10). To appraise the quality of the evaluations, the Oxford quality scoring system scale was employed. The extraction of information was carried out through the utilization of the participants, intervention, comparison, and outcomes (PICOS) format. The analysis encompassed research studies that implemented wearable devices during training and competitive events. Among elite field hockey competitions, GPS units were identified as the predominant wearable, followed by heart rate monitors. The intraclass correlation coefficient (ICC) related to wearable devices showed reasonably high between-trial ICCs ranging from 0.77 to 0.99. The utilization of wearable devices in field hockey primarily centers around the measurement of player activity profiles and physiological demands. The presence of discrepancies in sampling rates and performance bands makes it arduous to draw comparisons between studies. Nevertheless, this analysis attested to the fact that wearable devices are being employed for diverse applications in the realm of field hockey.

A novel hybrid supervised and unsupervised hierarchical ensemble for COVID-19 cases and mortality prediction

Though COVID-19 is no longer a pandemic but rather an endemic, the epidemiological situation related to the SARS-CoV-2 virus is developing at an alarming rate, impacting every corner of the world. The rapid escalation of the coronavirus has led to the scientific community engagement, continually seeking solutions to ensure the comfort and safety of society. Understanding the joint impact of medical and non-medical interventions on COVID-19 spread is essential for making public health decisions that control the pandemic. This paper introduces two novel hybrid machine-learning ensembles that combine supervised and unsupervised learning for COVID-19 data classification and regression. The study utilizes publicly available COVID-19 outbreak and potential predictive features in the USA dataset, which provides information related to the outbreak of COVID-19 disease in the US, including data from each of 3142 US counties from the beginning of the epidemic (January 2020) until June 2021. The developed hybrid hierarchical classifiers outperform single classification algorithms. The best-achieved performance metrics for the classification task were Accuracy = 0.912, ROC-AUC = 0.916, and F1-score = 0.916. The proposed hybrid hierarchical ensemble combining both supervised and unsupervised learning allows us to increase the accuracy of the regression task by 11% in terms of MSE, 29% in terms of the area under the ROC, and 43% in terms of the MPP metric. Thus, using the proposed approach, it is possible to predict the number of COVID-19 cases and deaths based on demographic, geographic, climatic, traffic, public health, social-distancing-policy adherence, and political characteristics with sufficiently high accuracy. The study reveals that virus pressure is the most important feature in COVID-19 spread for classification and regression analysis. Five other significant features were identified to have the most influence on COVID-19 spread. The combined ensembling approach introduced in this study can help policymakers design prevention and control measures to avoid or minimize public health threats in the future.

Emerging challenges in antimicrobial resistance: implications for pathogenic microorganisms, novel antibiotics, and their impact on sustainability.

Overuse of antibiotics is accelerating the antimicrobial resistance among pathogenic microbes which is a growing public health challenge at the global level. Higher resistance causes severe infections, high complications, longer stays at hospitals and even increased mortality rates. Antimicrobial resistance (AMR) has a significant impact on national economies and their health systems, as it affects the productivity of patients or caregivers due to prolonged hospital stays with high economic costs. The main factor of AMR includes improper and excessive use of antimicrobials; lack of access to clean water, sanitation, and hygiene for humans and animals; poor infection prevention and control measures in hospitals; poor access to medicines and vaccines; lack of awareness and knowledge; and irregularities with legislation. AMR represents a global public health problem, for which epidemiological surveillance systems have been established, aiming to promote collaborations directed at the well-being of human and animal health and the balance of the ecosystem. MDR bacteria such as E. coli, Staphylococcus aureus, Pseudomonas aeruginosa, Enterococcus spp., Acinetobacter spp., and Klebsiella pneumonia can even cause death. These microorganisms use a variety of antibiotic resistance mechanisms, such as the development of drug-deactivating targets, alterations in antibiotic targets, or a decrease in intracellular antibiotic concentration, to render themselves resistant to numerous antibiotics. In context, the United Nations issued the Sustainable Development Goals (SDGs) in 2015 to serve as a worldwide blueprint for a better, more equal, and more sustainable existence on our planet. The SDGs place antimicrobial resistance (AMR) in the context of global public health and socioeconomic issues; also, the continued growth of AMR may hinder the achievement of numerous SDGs. In this review, we discuss the role of environmental pollution in the rise of AMR, different mechanisms underlying the antibiotic resistance, the threats posed by pathogenic microbes, novel antibiotics, strategies such as One Health to combat AMR, and the impact of resistance on sustainability and sustainable development goals.

Molecular Epidemiology of Coronavirus Disease and its Effect on the Hematological Profile in District Kech, Balochistan

The coronavirus disease (COVID-19) is a respiratory disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This study aimed to investigate the occurrence of COVID-19 in district Kech, associated risk factors, clinical presentation, and its effect on blood cells. A structured questionnaire was designed to collect the data and the samples were investigated by RT-PCR. In total, 575 suspects were screened, among which 64 (11.16%) had COVID-19 infection, 40.6% were males, and 59.4% were females. An increased positivity of 53.12% was measured in the younger age group (15-30 years) and the lowest (18.75%) was noticed in elders > 50 years. 95.3% of the patients were newly infected, and 7.7% had a contact history with COVID-19-infected patients. The clinical symptoms, such as fever, cough, nausea, vomiting, and diarrhea, were identified in 89.1%, 67.2%, 51.6%, 46.9%, and 12.5%, respectively. The prominent clinical features, like fever, cough, nausea, diarrhea, chest distress, chest pain, and psychological stress were observed. Noticeably, 10.9% of obesity and 7.8% of asthma patients were co-infected with COVID-19 disease including 39.1% of cases showed psychological trauma. Leucocytosis and a decrease in hemoglobin concentration and platelets were determined in COVID-19-infected patients. A significant effect was observed on the hematological profile, however, the effect was severe in the older age group (>50 years). The results suggest that the large population of the study area is infected by SARS-CoV-2, appealing to the need for surveillance on a large scale and the implementation of preventive measures to control further dissemination of the disease.

The Prevalence of Risk Factors for Cardiovascular Diseases in Najran Region, Saudi Arabia

The primary goal of this study was to investigate the knowledge, prevalence, and risk factors of cardiovascular diseases among individuals in the Najran region of Saudi Arabia. In the Najran region of Saudi Arabia, an online cross-sectional survey was conducted. Between September and October 2023, a self-administered questionnaire was distributed to a random sample of the general population aged 18 and up. The survey instrument asked about history and exposure, physician-diagnosed illnesses, cardiovascular diseases (CVDs), medication use, and other risk factors. This research had a total of 2046 individuals. Around one-fifth of the study participants reported that they or a family member suffered from CVD, and arrhythmia was the most commonly reported; blood tests, cardiac catheterization, and ECG were the most commonly reported tests performed for CVD patients, around one-tenth of CVD patients reported that they do not have any chronic diseases other than CVD, and the vast majority of the patients confirmed their regular medical appointments. This is one of the first studies to investigate the knowledge, prevalence, and use of CVD drugs among individuals in the Najran region of Saudi Arabia. The study participants’ lack of knowledge about CVD could lead to ineffective preventive measures and poor patient outcomes. The study’s findings underscore the crucial need for more extensive and efficient educational initiatives that consider the targeted population’s talents, attitudes, and perceptions.

Occupational injuries caused by fire and smoke in Victoria, Australia, 2003–2021: a descriptive study

ObjectivesHospital attendance related to fire, flame or smoke exposure is commonly associated with work. The aim of this study was to examine time trends and risk factors for work-related fire/flame/smoke...

Therapeutic Advancement in Treatment and Prevention of Nipah Viral Infection: A Review

The Nipah virus (NiV) is an emerging zoonotic pathogen that poses a major risk to global health, with a high mortality rate and the potential for wide outbreaks. NiV, which originated in fruit bats, has shown a concerning potential to infect humans and cause serious respiratory and neurological disorders. The virus has a pleomorphic structure and a broad host range, preventing efforts to understand and regulate its pathogenesis. This review discusses current advances in the prevention and management of NiV, including the efficacy of several antiviral therapies in vitro and in vivo. Treatments such as Ribavirin, Favipiravir, Acyclovir, Remdesivir, and Balapiravir have produced varying results, whilst monoclonal antibodies such as m102.4, h5B3.1, and nAH1.3 provide effective neutralization but require additional testing in humans. In addition, innovative vaccination techniques such as recombinant measles virus, subunit vaccines, vector vaccines, and the novel mRNA-1215 vaccine have shown success in preclinical and early clinical trials. To reduce the risk of human transmission, preventive measures include early outbreak detection through improved surveillance systems, exposure-based screening, and educational activities. This covers vital guidelines like avoiding raw date palm sap during outbreak seasons and using physical barriers to prevent bat-to-human transmission, which is vital for controlling this deadly virus.

Physical Fitness and Risk of Mental Disorders in Children and Adolescents

With the rising prevalence of mental disorders among children and adolescents, identifying modifiable associations is critical. To examine the association between physical fitness and mental disorder risks. This nationwide cohort study used data from the Taiwan National Student Fitness Tests and National Health Insurance Research Databases from January 1, 2009 to December 31, 2019. Participants were divided into 2 cohorts targeting anxiety and depression (1 996 633 participants) and attention-deficit/hyperactivity disorder (ADHD; 1 920 596 participants). Participants were aged 10 to 11 years at study entry and followed up for at least 3 years, had a nearly equal gender distribution, and an average follow-up of 6 years. Data were analyzed from October 2022 to February 2024. Assessments of physical fitness included cardiorespiratory fitness (CF), muscular endurance (ME), muscular power (MP), and flexibility, measured through an 800-m run time, bent-leg curl-ups, standing broad jump, and sit-and-reach test, respectively. Kaplan-Meier method calculated the cumulative incidence of anxiety, depression, and ADHD across fitness quartiles. Additionally, multivariable Cox proportional hazards models were used that included all 4 fitness components and explored sex and income as modifiers. The anxiety and depression cohort had 1 996 633 participants (1 035 411 participants were male [51.9%], and the median [IQR] age was 10.6 [10.3-11.0] years), while the ADHD cohort had 1 920 596 (975 568 participants were male [51.9%], and the median [IQR] age was 10.6 [10.3-11.0] years). Cumulative incidence of mental disorders was lower among participants in better-performing fitness quartiles, suggesting a dose-dependent association. Gender-specific analyses, controlling for confounders, revealed that improved CF, indicated by a 30-second decrease in run times, was associated with reduced risks of anxiety, depression, and ADHD in female participants, and lower risks of anxiety and ADHD in male participants (adjusted hazard ratio [aHR] for ADHD risk for female participants, 0.92; 95% CI, 0.90-0.94; P < .001; for male participants, 0.93; 95% CI, 0.92-0.94; P < .001). Enhanced ME, marked by an increase of 5 curl-ups per minute, was associated with decreased risks of depression and ADHD in female participants, and lower anxiety and ADHD risks in male participants (aHR for ADHD risk for female participants, 0.94; 95% CI, 0.92-0.97; P < .001; for male participants, 0.96; 95% CI, 0.95-0.97; P < .001). Improved MP, reflected by a 20-cm increase in jump distance, was associated with reduced risks of anxiety and ADHD in female participants and reduced anxiety, depression, and ADHD in male participants (aHR for ADHD risk for female participants, 0.95; 95% CI, 0.91-1.00; P = .04; for male participants, 0.96; 95% CI, 0.94-0.99; P = .001). This study highlights the potential protective role of cardiorespiratory fitness, muscular endurance, and muscular power in preventing the onset of mental disorders. It warrants further investigation of the effectiveness of physical fitness programs as a preventive measure for mental disorders among children and adolescents.

Deep Learning Models for Type 2 Diabetes Detection in Saudi Arabia

One of the predominant health issues affecting Saudi Arabia and leading to many complications is Type 2 diabetes (T2D). Early detection and significant preventative measures lead to curbing and controlling the health issue. There are fewer datasets in the literature for the detection of T2D in the Saudi population. Past studies using Saudi data have favoured machine learning algorithms to classify T2D. Although the application of this data in machine learning is evident, no studies exist in the literature that compare this data, especially those related to deep learning algorithms. This study's objective is to use specific Saudi data to develop multiple deep learning models that could be used to detect T2D. The research uses a Deep Neural Network (DNN), an Autoencoder (AE), and a Convolutional Neural Network (CNN) to create predictive models and compare their performance with a traditional machine learning classifier used on the same dataset that outperformed other machine learning algorithms such as a Decision Forest (DF). Various metrics were used to evaluate the effectiveness of the models, such as accuracy, precision, recall, F1 score and area under the ROC curve (AUC) where the ROC acts as a receiver operating characteristic curve. There are two cases in this paper: (i) uses all features of the dataset and (ii) uses six of the ten features, such as DF. In case (i), the results were shown that AE outperformed other models with the highest accuracy for imbalanced and balanced data 81.12\% and 79.16\%, respectively. The results for case (ii) showed that AE scored the highest 81.01\% accuracy with imbalanced data compared to DF and DF achieved the highest accuracy of 82.1\% with balanced data. As a result, both cases explored in this study revealed that AE has a constant superior performance if imbalanced data is used. In contrast, DF demonstrated the highest accuracy when a balanced dataset was used with a feature set reduction. They help to identify the undiagnosed T2D, and they are essential for professionals in Saudi Arabia in the health sector to promote health connections, identify risks and contain or improve their diabetes management.

An Analysis of Verification Systems and Cybersecurity Dangers

Global infrastructure provides all nations essential services such as Internet, electricity, banking, finance, public services, transportation, and water management. Each country has a distinct plan for critical infrastructure based on its sector. As IoT-based solutions become more prevalent, critical infrastructures require network and Internet access. As a result, critical systems within information networks are also vulnerable to cyber-attacks. Identifying possible cyber-attacks, developing defence tactics, and implementing preventative measures are critical. Protecting critical infrastructures from cyber-attacks is crucial nowadays. This paper examines current attacks on critical infrastructures. Security steps are addressed to prevent Internet protocol-based innovations. The IoT has enabled online connectivity for almost anything. The Internet of Things (IoT) refers to networked computing devices that may send data without human input. In contrast, the Internet is valuable; it can pose a significant cybersecurity risk to critical infrastructure.

Antibacterial Screening of Medicinal Plant Extracts against Staphylococcus aureus and Escherichia coli

Herbal remedies are crucial for treating bacterial infections due to antibiotic resistance, with numerous studies demonstrating their antibacterial properties against various harmful species. This study investigates the antibacterial properties of an aqueous extract from 40 medicinal plants in vitro, assessing their effectiveness against Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria. The well diffusion method was employed to assess the antibacterial activity. Six plants exhibit antibacterial properties against the two bacterial strains among these extracts. Guava (Psidium guajava) and Clove (Syzygium aromaticum)cold water extracts were the most effective plant extracts against Escherichia coli, with inhibition zones of 6.2 mm and 5.2 mm, respectively. Coriander (Coriandrum sativum) leaves and Sana makki (Cassia angustifolia) leaves cold water extracts were the most effective plant extracts against Staphylococcus aureus with an inhibitory effect with inhibition zones of 6.9 mm and 5.9 mm respectively. The plant extracts differ in antibacterial activities against S. aureus and E. coli. However, Extracts of Senna alata, Tamarindus indica, Psidium guajava, Syzygium aromaticum, and Cassia angustifolia showed inhibitory activity against both of the microorganisms tested. These potentially useful plant extracts can be utilized as natural alternatives to preventive measures for food poisoning and preservation, thereby avoiding the health risks associated with chemically antibacterial agents. These antibacterial properties encourage future research into new chemical compositions that can help treat or cure some diseases.

Assessment and Grading of Accredited Social Health Activist Workers Based on Simulation, Awareness, and Writing Skills in Urban and Rural Karnataka: A Comparative Study

Introduction: Accredited Social Health Activist (ASHA) workers and their activities are regarded as a critical component linking the community and health-care facilities. They are the cornerstone of the Indian public health-care system responsible for spreading awareness and recommending preventive measures in the community. This study aims to assess the awareness, writing skills, and practical-based performance of the ASHA workers in urban and rural Karnataka. Materials and Methods: A cross-sectional study was conducted among ASHA workers in rural and urban Mysore district. A multistage sampling technique was adopted for selecting the participants. The ASHA workers were asked to fill out a pretested semi-structured questionnaire. An unpaired t-test was used for inferential statistics. P &lt; 0.05 was considered statistically significant. Results: The mean age of the workers in urban areas was 36.38 ± 5.877 years, while in rural, it was 41.53 ± 6.755 years. The overall average score for rural ASHA workers was more (70.49 ± 14.018) when compared to the urban ASHAs (65 ± 13.400). The average years of experience were 6.14 ± 1.44 years in urban and 10.5 ± 2.66 years in rural areas. The daily working hours ranged from 3 to 10 h in urban and 2 to 10 h among rural ASHA workers. Conclusion: The overall score of rural ASHA workers was higher when compared to urban ASHAs. Even though the grading and performance of the ASHA workers were good, their expertise in identifying and tackling life-threatening conditions remains inadequate. This can be improved with more vigilant and periodic training and monitoring along with periodic recruitment at regular intervals.

Local government resilience in the face of Russian aggression: the case of Ukraine

Local government resilience in the face of Russian aggression: the case of Ukraine