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This study investigated the degree of practicing soft skills by science teachers using the descriptive approach. To achieve the study's objective, an observation card was developed. It was used to monitor three lessons for each subject (n=60) science teachers, who were distributed into six groups according to work experience and educational qualification, in the Directorate of Education of Bani Kinanah District in Irbid Governorate. The results showed that science teachers practice soft skills such as communication, problem-solving, negotiation, planning and time management, teamwork, leadership, and critical thinking to a high degree, with an explained variance (9.13%), on all dimensions of the observation card. However, the results also indicated statistically significant differences ([alpha] = 0.05) between the arithmetic means of the teaching practices of soft skills among science teachers resulting from the different levels of educational qualification and teaching experience. Thus, teachers with educational qualifications typically practice soft skills to a greater extent with an average level of (14.48%) than their peers without educational degrees. Teachers with advanced experience are more likely to exercise soft skills with an average level of (11.73%) than their counterparts with medium and simple experience. Therefore, the study recommended including soft skills practice as a university course, endorsing it in universities, and continuous training for science teachers on teaching practices for soft skills through training courses and workshops.

The number of individuals with dementia is on the rise, highlighting the need to create effective educational methods that can improve nursing students' understanding and attitude toward this group of people who require special care. Explore the effectiveness of introducing a new curricular course in improving nursing students' knowledge of and attitudes toward people living with dementia and the provision of care for them. A pretest-posttest quasi-experimental design was used. After the introduction of dementia lectures, both study groups had a significant improvement in knowledge and attitude toward people living with dementia (P [less than or equal to] 0.05). Adding clinical experience did not significantly enhance knowledge. It improved attitudes, but the result was not statistically significant (P > 0.05). The introduction of a new curricular course had a positive impact on the knowledge of and attitudes of nursing students toward people living with dementia. These findings emphasize the importance of incorporating dementia-focused education to enhance the quality of care provided by future nursing professionals.

Mononuclear Fe ions ligated by nitrogen (FeNx) dispersed on nitrogen-doped carbon (Fe-N-C) serve as active centers for electrocatalytic O2 reduction and thermocatalytic aerobic oxidations. Despite their promise as replacements for precious metals in a variety of practical applications, such as fuel cells, the discovery of new Fe-N-C catalysts has relied primarily on empirical approaches. In this context, the development of quantitative structure-reactivity relationships and benchmarking of catalysts prepared by different synthetic routes and by different laboratories would be facilitated by the broader adoption of methods to quantify atomically dispersed FeNx active centers. In this study, we develop a kinetic probe reaction method that uses the aerobic oxidation of a model hydroquinone substrate to quantify the density of FeNx centers in Fe-N-C catalysts. The kinetic method is compared with low-temperature Mössbauer spectroscopy, CO pulse chemisorption, and electrochemical reductive stripping of NO derived from NO2- on a suite of Fe-N-C catalysts prepared by diverse routes and featuring either the exclusive presence of Fe as FeNx sites or the coexistence of aggregated Fe species in addition to FeNx. The FeNx site densities derived from the kinetic method correlate well with those obtained from CO pulse chemisorption and Mössbauer spectroscopy. The broad survey of Fe-N-C materials also reveals the presence of outliers and challenges associated with each site quantification approach. The kinetic method developed here does not require pretreatments that may alter active-site distributions or specialized equipment beyond reaction vessels and standard analytical instrumentation.

Abstract Background The COVID-19 pandemic necessitated an abrupt transition to online learning in nursing education, presenting unprecedented challenges. This research aims to comprehensively assess the challenges faced by nursing students during this transition, exploring key issues, recommending strategies, and analyzing their impact on student perceptions. Methods Using a cross-sectional design, the study surveyed 941 nursing students across eight Arab countries—Jordan, Iraq, Lebanon, Palestine, Oman, KSA, UAE, and Egypt—to ensure a representative sample and enhance external validity. Data collection involved a thorough survey covering academic, technological, and administrative challenges. Reliability analysis, descriptive statistics, and variance analysis using Kruskal -Wallis and Mann–Whitney tests were conducted to examine differences between countries and sociodemographic variables. Results Descriptive statistics revealed significant demographic disparities. Single individuals in Jordan and those with lower family income in Palestine and Lebanon reported notably higher challenges. Female students in Iraq and Lebanon perceived greater challenges compared to males. Students pursuing diplomas in Jordan and bridging programs in Lebanon faced elevated difficulties. Governmental university students in Lebanon and private university students in Jordan encountered distinct challenges. Lack of available internet was particularly challenging in Jordan and Lebanon, whereas students using tablets in Lebanon and laptops in Palestine reported heightened challenges. Economic disparities, notably in family income, further hindered engagement with online learning materials. Across countries, academic challenges included managing coursework and accessing resources, exacerbated by administrative inefficiencies, especially in Palestine and Lebanon. Students in the UAE reported fewer challenges, facilitated by robust internet infrastructure and comprehensive institutional support. Conclusion This study provides critical insights into the challenges faced by nursing students during the Middle East's online learning transition. Key challenges encompass technological issues, academic workload, and administrative inefficiencies, with significant disparities across countries. The findings underscore the urgent need for targeted interventions, particularly in Palestine, to enhance online learning experiences. Policymakers and educational institutions can leverage these insights to advocate for student-centric approaches and policy development aimed at improving online learning across the region.

BACKGROUND AND OBJECTIVES: Municipal solid waste emerges as a pressing concern for environmental management and sustainability, particularly in urban areas with high rates of population growth and limited infrastructure. This study aims to assess the outputs and benefits of a separate source collection system, which separates recyclable materials at their point of origin. The study highlights the consequences of separate source collection on the community''s economic, environmental and social context. The study forms part of a project that intends to upscale sustainable and efficient waste management approaches in a transition towards a circular economy model that utilizes and recycles waste and materials. The objectives encompass addressing urban challenges and providing key insights for environmental management and sustainability through separate source collection systems that improve efficiency, reduce cost and encourage sustainable community practices.METHODS: The study was implemented in the Al-Radwan neighborhood in Amman, Jordan, and included 8,460 individuals and 3,124 households. Data on waste generation from residential and commercial activities were analyzed and used to design the separate source collection system, which included public awareness campaigns for individuals in the study area, waste composition investigations and maps for routes of waste collection trucks. Yellow and grey bins were used to collect recyclable and residual waste, respectively. Data on waste amount and composition were collected and interpreted for the 2020-2023 period. Data on fuel consumption, maintenance and depreciation were used to calculate the operational costs of separate source collection and the old system of municipal solid waste collection. Ground data were analyzed in terms of the individual''s and households'' adoption of waste-sorting practices. An overall assessment was carried out for the economic benefit of separate source collection.FINDINGS: Analyses of waste generation in the study area showed that the average quantity of municipal waste was 0.89 kilogram per capita per day, and there is a trend that shows an increase in municipal solid waste quantities with respect to time. A significant amount of municipal solid waste (60 percent) has an organic composition, while recyclable waste constitutes about 12.5 percent of the total municipal solid waste. The study was a success, with a consistent increase in recyclable waste collection at 59 percent average purity and a 30 percent decrease in total yearly waste collection costs. The project contributed to job creation and improved community participation in municipal solid waste management. The beneficial impacts of awareness campaigns were the low level of required maintenance with respect to the separate source collection system and the high level of public participation and cooperation, particularly in municipal solid waste sorting.CONCLUSION: The study highlighted the importance and effectiveness of the innovative separate source collection system and showed its economic and social benefits while considering its positive environmental impacts. The findings confirmed the system''s economic viability and applicability, showing its potential for large-scale adoption in Jordan. The adoption and implementation of separate source collection will be highly emphasized as it will be needed for solving issues associated with municipal solid waste via creative solutions that promote sustainability and community well-being.

Abstract Background Fatigue among patients with end-stage kidney disease (ESKD) receiving haemodialysis imposes a substantial burden on patients’ quality of life and expected treatment outcomes. This study explores the perspective on ESKD-related fatigue and contributing factors among Omani patients receiving haemodialysis. Methods An exploratory qualitative design was used. Participants (N = 25) were recruited from two Omani haemodialysis centres, and data were collected through semi-structured interviews, which were transcribed and analysed using a thematic analysis approach. NVivo 11 is used to manage qualitative data and create memos, nodes, and codes. Results Findings highlighted three themes: (i)“Inevitability of fatigue,” (ii)“Contributors to physical fatigue,” and (iii)“Contributors to mental fatigue.” Theme one alluded to the inevitability of fatigue and the unique experience encountered by patients. Theme two addressed the physical fatigue associated with ESKD-related factors, such as chronically low haemoglobin levels, and the exhausting impact caused by the frequency and travelling distance for treatment sessions. Theme three, mental fatigue, was notably driven by heightened emotional disturbance, encompassing frustration, guilt, anxiety, and distress, that in turn impacted family interactions, frequently triggering anger and remorse. Moreover, mental fatigue is a result of disturbances in expressing physical sexuality in marriage, as physical fatigue was found to be a significant contributor to unsatisfactory sexual experiences and, thus, straining the relationships between couples. Conclusions This study offers an explanation of fatigue among Omani patients with ESKD who are receiving haemodialysis. The study emphasises close links between physiological change, the haemodialysis process, and mental tiredness, together with their contribution to supporting the need for a holistic approach and care strategies in managing these patients and promoting patient and family well-being.

Abstract The global incidence of gout has increased rapidly, likely secondary to the increase in the prevalence of conditions that predispose to gout, such as obesity. Depending on the population studied, the prevalence of gout ranges from less than 1 to 6.8%. Thus, gout can be a significant burden on healthcare systems. The objective of this study is to observe the trends in the incidence, prevalence, and disability-adjusted life years (DALYs) of gout between 1990 and 2019 globally and in the European Union (EU) 15+ nations. We extracted data from the Global Burden of Disease Study database based on the International Classification of Diseases (ICD) versions 10 and 9. Incidence, prevalence, and disability-adjusted life years (DALYs) were extracted for individual EU15+ countries and globally in males and females between 1990 and 2019. Joinpoint regression analysis was used to describe trends. Between 1990 and 2019, gout prevalence, incidence, and DALYs increased in both males (+ 21.42%, + 16.87%, + 21.49%, respectively) and females (+ 21.06%, + 18.75%, + 20.66%, respectively) globally. The United States of America had the highest increase in prevalence (males: + 90.6%; females + 47.1%), incidence (males: + 63.73%; females: + 39.11%) and DALYs (males: + 90.43%; females: + 42.75%). Incidence, prevalence, and DALYs from gout are increasing worldwide and in most of the EU15+ countries for males and females. Studies have reported the association of gout with comorbidities such as metabolic syndrome, diabetes mellitus, and cardiovascular disease. Health policies and resource allocation are required to increase awareness and modify risk factors globally.

The effect of different irrigation methods (sprinkler, surface, surface-drip, and subsurface-drip) using treated wastewater, on alfalfa yield quantity and quality, was studied under semi-arid conditions. Randomized complete block design considering irrigation methods on 5 × 5 m plots replicated four times. Applied irrigation water was based on the Penman–Monteith equation using the FAO Cropwat software and accounting for the efficiencies of used irrigation systems. Surface irrigation gave the highest alfalfa fresh yield without significant difference compared to subsurface-drip. Average fresh production was 123, 120, 109, and 91 tons/h for surface, subsurface-drip, surface-drip, and sprinkler irrigation, respectively. Alfalfa fresh weight from subsurface-drip irrigation was 32 and 10% higher compared to sprinkler and surface-drip irrigation. Alfalfa dry weight from subsurface-drip irrigation was 10, 21, and 47% higher compared to surface-drip, surface, and sprinkler irrigation, respectively. N percentage in alfalfa leaves was significantly lower by 12% under subsurface-drip irrigation as compared to the other irrigation methods. Escherichia coli (E. coli) and fecal coliform (FC) were not detected on alfalfa leaves using subsurface-drip irrigation. E. coli and FC counts were high on leaves using sprinkler and surface irrigation. Subsurface-drip irrigation may be adapted as an efficient irrigation method when using non-conventional water under semi-arid conditions. HIGHLIGHTS Irrigation study: Examined methods using treated wastewater in semi-arid areas.; Subsurface-drip: Tops in dry yield, matches in fresh yield.; Health benefits: Subsurface-drip reduces E. coli and fecal coliform on alfalfa.; Smart water use: Advocates calculated use with FAO Cropwat insights.; Alternative water: Recommends subsurface-drip for treated wastewater in semi-arid regions.;

Abstract Background The ability of a nurse to make effective clinical decisions is the most important factor that can affect the treatment quality. However, several factors can affect the ability of nursing and midwifery students to make effective clinical decisions. Objectives This study aims to identify the confounding factors that may affect the clinical decision making of nurses and thus patient outcomes after the COVID-19 pandemic in Jordan. Methods A descriptive cross-sectional design was employed in this study. An online self-administered questionnaire was distributed to 269 nursing and midwifery students selected through purposive sampling, 224 of whom completed the questionnaire. The valid and reliable nursing decision-making instrument, which consisted of 24 items, was employed to gather the data, and descriptive statistics and simple linear regression were employed for the data analysis. Data was collected from November to the end of December 2022. Results Among the respondents, 72.8% were female, and the average age was 20.79 years (SD = 1.44). The vast majority of the respondents (94.6%) was unmarried, and 74.1% were pursuing a nursing degree. The simple linear regression analysis showed that clinical decision making had a negative and significant relationship with social media usage of an average of 6 h a day (β=−0.085). Moreover, the male nursing students obtained lower clinical decision-making scores (β= −0.408) compared with the female nursing students. Conclusion Social media usage and gender have a considerable effect on the clinical decision making of the nursing and midwifery students. Therefore, the confounding factors that can affect the clinical decision making of nurses should be discussed further, and strategies to address such factors should be implemented.

Abstract In this present work, the preparation of ternary MoS2–NiO–CuO nanohybrid by a facile hydrothermal process for photocatalytic and photovoltaic performance is presented. The prepared nanomaterials were confirmed by physio-chemical characterization. The nanosphere morphology was confirmed by electron microscopy techniques for the MoS2–NiO–CuO nanohybrid. The MoS2–NiO–CuO nanohybrid demonstrated enhanced crystal violet (CV) dye photodegradation which increased from 50 to 95% at 80 min; The degradation of methyl orange (MO) dye increased from 56 to 93% at 100 min under UV–visible light irradiation. The trapping experiment was carried out using different solvents for active species and the Z-Scheme photocatalytic mechanism was discussed in detail. Additionally, a batch series of stability experiments were carried out to determine the photostability of materials, and the results suggest that the MoS2–NiO–CuO nanohybrid is more stable even after four continuous cycles of photocatalytic activity. The MoS2–NiO–CuO nanohybrid delivers photoconversion efficiency (4.92%) explored efficacy is 3.8 times higher than the bare MoS2 (1.27%). The overall results indicated that the MoS2–NiO–CuO nanohybrid nanostructure could be a potential candidate to be used to improve photocatalytic performance and DSSC solar cell applications as well.

The current presentation aims to identify the extent to which the ornaments and colors of the Asiri art Qatt influence in highlighting the social culture of the southern region, and to identify the distinctive character of the Asiri folklore. This research used both the inductive and analytical method, and a questionnaire was applied to a sample of (111) individuals from the southern region. The results of this research: There is a significant impact of the ornaments and colors of the Asiri Qatt in highlighting the cultural highlight of the southern region, and that there are great benefits to the signs of geometric designs and colors in the art of the Asiri Qatt; The commercial nature of models and printing could create a potential for a rise in contemporary painting. From Al-Asiri wall art (The Qatt) suitable for modern designs.

Missing data occurs frequently in sample surveys. Numerous imputation techniques have been proposed to tackle the problem of missing data, and, in fact, limited works are available in the literature to deal with the issue of missingness while the data are ridden with measurement errors (ME). In addition, no work has been done on the robustness to handle the issue of missing data when it is contaminated with correlated measurement errors (CME). This article proposes some robust imputation methods (RIM) to impute the missing data in the presence of CME. The mean square error (MSE) of the proposed RIM is derived from the first-order approximation and examined with the MSE of the conventional imputation methods. The results are theoretically established and explained using a vast simulation study. Two applications of real data sets are presented to illustrate the efficiency and superiority of the suggested estimators relative to some estimators considered in this study.

The aim of this study was to discern the students' perception of social media networks integration into the educational process. The study was conducted in seven universities in the Northern region of Jordan. To achieve this goal, authors used the descriptive survey approach. A stratified random sample of 762 students from both genders and different disciplines were targeted. For data collection purposes, a survey tool was designed, which consisted of one polar question, one open question and a questionnaire consisting of fifteen 5-point Likert scale paragraphs. Results indicated that 82.41% of respondents showed constructive attitudes toward the integration of social media to the educational process and indicated their top preferred social media applications. Furthermore, the findings revealed that there was a significant relationship between use behaviour and behavioural intentions, as well as a significant relationship between use behaviour and facilitating conditions. Finally, the results showed no significant statistical difference at [alpha] = 0.05 between the respondents' statistical means pertaining to students' gender or field of study.

This study aimed to evaluate the effect of a family-based lifestyle intervention on reducing body weight among Jordanian children with obesity aged 6–9 years old. The pretest-posttest control group design was conducted among 162 children (75 in the intervention group and 87 in the control group) with obesity aged 6–9 years old at four primary schools in Jordan during the period from March 2021 to July 2021. The results found that, after the intervention, there was a statistically significant change in the F scores in the control group vs. in the intervention group (M = 37.07, SD = 2.77; M = 33.48, SD = 2.73; t (160) = 8.29, P < 0.001), where the mean BMI percentile was reduced by 2.05 in the intervention group. A significant difference was demonstrated in the median BMI percentile in the intervention and control groups post-intervention (P < 0.001). A significant difference was also noticed between the average weekly reported dietary habits and the physical activities of both the control group and the intervention group post-intervention. The findings support the effect of family-based lifestyle interventions. Healthcare providers should adopt such interventions for children living with obesity. Future study is required to evaluate the long-term effectiveness of this intervention on weight reduction.

Abstract Assessing unmet needs is crucial to achieving quality care and patient satisfaction. Between September and December 2021, we assessed unmet supportive care needs in a consecutive sample of adult survivors of childhood cancer at KHCC (King Hussien Cancer Center). Two hundred and ninety-seven adult survivors of childhood cancer completed the study questionnaire. The average needs score across all domains was 24.80 (SD = 19.65), with the financial domain scoring the highest 30.39 (SD = 31.95) and sexuality scoring the lowest 7.67 (SD = 19.67). Using a multivariate linear regression model, female gender was independently associated with significantly high scores in all need domains (p

BACKGROUND: This narrative review aims to explore the current state and future perspective of artificial intelligence (AI) in respiratory care. The objective is to provide insights into the potential impact of AI in this field. METHODS: A comprehensive analysis of relevant literature and research studies was conducted to examine the applications of AI in respiratory care and identify areas of advancement. The analysis included studies on remote monitoring, early detection, smart ventilation systems, and collaborative decision-making. RESULTS: The obtained results highlight the transformative potential of AI in respiratory care. AI algorithms have shown promising capabilities in enabling tailored treatment plans based on patient-specific data. Remote monitoring using AI-powered devices allows for real-time feedback to health-care providers, enhancing patient care. AI algorithms have also demonstrated the ability to detect respiratory conditions at an early stage, leading to timely interventions and improved outcomes. Moreover, AI can optimize mechanical ventilation through continuous monitoring, enhancing patient comfort and reducing complications. Collaborative AI systems have the potential to augment the expertise of health-care professionals, leading to more accurate diagnoses and effective treatment strategies. CONCLUSION: By improving diagnosis, AI has the potential to revolutionize respiratory care, treatment planning, and patient monitoring. While challenges and ethical considerations remain, the transformative impact of AI in this domain cannot be overstated. By leveraging the advancements and insights from this narrative review, health-care professionals and researchers can continue to harness the power of AI to improve patient outcomes and enhance respiratory care practices. IMPROVEMENTS: Based on the findings, future research should focus on refining AI algorithms to enhance their accuracy, reliability, and interpretability. In addition, attention should be given to addressing ethical considerations, ensuring data privacy, and establishing regulatory frameworks to govern the responsible implementation of AI in respiratory care.

Technology implementation can significantly benefit organizations, but ensuring it aligns with their business needs and goals is crucial. Adopting an enterprise architecture approach can aid healthcare enterprises in overcoming challenges during the transformation process. In particular, this study examines how The Open Group Architecture Framework (TOGAF) can facilitate digital transformation while ensuring alignment with business needs. Using the Architecture Development Method (ADM) of TOGAF, the study analyzes the current architecture of the National Center for Diabetes, Endocrinology, and Genetics (NCDEG) in Jordan, intending to develop a target architecture that helps NCDEG effectively achieve its goals. [JJCIT 2024; 10(2.000): 182-197]

To define useful numbers having values from 0 to 1, as percentages, probabilities, and proportions, the unit probability models are often employed in probability and statistics. In this paper, a new two-parameter model on the unit interval, entitled the unit Mirra distribution (UMD) is suggested which is a modification of the Mirra distribution (MD). Various statistical properties of the proposed UMD as the rth moment, variance, inverse moments, and incomplete moments are presented. Also, the distributions of order statistics, coefficients of variation and skewness, stochastics ordering, and median and mean deviations are provided. The reliability functions such the hazard function, survival function, odds function, reversed hazard rate function, and the mean residual function are provided with supported graphical representation. The Lorenz curve, Gini index, and Bonferroni curve of the UMD with some simulations are included. The distribution parameters are estimated based on the maximum likelihood estimation, ordinary least squares estimation, Anderson-Darling and maximum product of spacing’s estimation. Finally, two different applications of actual data sets that represent the times to infection of kidney dialysis patients in months and the trade share data on unit interval are carried out to evaluate the model's performance as compared to some competitors. It turns out that the suggested UMD can serve as a good alternative for modeling these data sets.

Aims: This in-vitro study aimed to evaluate the effect of microwave irradiation on polyvinyl siloxane impression material contaminated with candida Albicans. Materials and methods: 30 samples were fabricated from the acrylic mold with disk shape 5*2 (diameter*thickness). Samples incubated with Brain Heart Infusion Broth (BHI) media containing Candida albicans. Then were divided into 30 samples into 6 groups: C (positive control); 5 non-irradiated specimens, 3MWD ( samples irradiated for 3minute in dry condition), 6MWD (samples irradiated for 6minute in dry condition), 3MWW (samples irradiated for 3minute in wet condition), 6MWW (samples irradiated for 6minute in wet condition), CHX (samples immersed in 0.5% chlorhexidine) After incubation of all samples for 24 hours at 37°C, the samples were got vortex and then serial dilution carried out of suspensions then cultured on Sabouraude Dextrose Agar after incubation for 24 hours at 37°C bacteria were counted. A further 7 days of incubation for microwaved samples was done to verify the effectiveness of both dry and wet microwave sterilization for two periods of time. Results: There was a significant reduction in cfu /ml of candida albicans at 24 hours of incubation. No growth of C. albicans was recorded after 7 days of incubation. Conclusions: Microwave irradiation at 640W for both wet and dry conditions for 3 and 6 min was proved to be effective in the disinfection of polyvinyl siloxane specimens contaminated with. Candida. albicans.

The concept of operators in topological spaces occupies a very important place. For this reason, a great deal of work and many results were presented via operators. Herein, we defined a primal local soft closure operator $ \Lambda(\cdot) $ using the concept of soft topology and soft primal and reconnoitered its basic characteristics. Then, we found several fundamental results about the behavior of the primal soft closure operator $ \lambda{(\cdot)} $ with the help of $ \Lambda(\cdot). $ Among other obtained results, we introduced a new topology induced by the primal soft closure operator. At last, we defined primal soft suitable spaces and gave some equivalent descriptions of it.

Aims: The study aimed to investigate the effect of sterilization by microwave irradiation at 640W on the surface roughness of polyvinyl siloxane. Materials and methods: 30 samples of addition silicone impression material with a thickness of 20mm and 3mm as diameter. The acrylic mold was used for the samples' fabrication. The samples were divided into six groups each group had five specimens (C) control (3MWD) Samples irradiated for 3minute in dry conditions, (6MWD) samples irradiated for 6minute in dry conditions, (3MWW) samples irradiated for 3minute in wet condition, (6MWW) samples irradiated for 6minute in wet condition and (CHX) samples immersed in chlorhexidine with 0.5% concentration for one hour. A profilometer (Talysurf 10, R.P.I. LTD, Metrology Division) is used for measuring surface roughness by taking the means of three points with the aid of a stylus. Results: There were statistical differences between the control group and the tested groups. Mann-Whitney showed that only 3MWD had no statistical differences from the control group. Conclusions: Disinfection of polyvinyl siloxane using the microwave at 640W for 3 minutes is safe or recommended regarding its least effect on the surface roughness.

Abstract This paper introduces a novel approach for detecting the SARS-CoV-2 recombinant spike protein combining a label free electrochemical impedimetric immunosensor with the use of purified chicken IgY antibodies. The sensor employs three electrodes and is functionalized with an anti-S IgY antibody, ELISA and immunoblot assays confirmed the positive response of chicken immunized with SARS-CoV2 S antigen. The developed immunosensor is effective in detecting SARS-CoV-2 in nasopharyngeal clinical samples from suspected cases. The key advantage of this biosensor is its remarkable sensitivity, and its capability of detecting very low concentrations of the target analyte, with a detection limit of 5.65 pg/mL. This attribute makes it highly suitable for practical point-of-care (POC) applications, particularly in low analyte count clinical scenarios, without requiring amplification. Furthermore, the biosensor has a wide dynamic range of detection, spanning from 11.56 to 740 ng/mL, which makes it applicable for sample analysis in a typical clinical setting.