Face Challenges Research Articles

Unravelling the complexity of research capacity strengthening for health professionals in low- and middle-income countries: A concept analysis.

Research capacity strengthening (RCS) is crucial in enhancing healthcare outcomes, particularly in low- and middle-income countries (LMICs), which face challenges due to limited resources, unequal access to care and the need for evidence-based decision-making. We seek to move beyond a surface-level understanding of RCS, unearthing the core attributes, the factors that precede its implementation and the transformative outcomes it generates within the LMIC healthcare landscape. This study employs the Walker and Avant approach to concept analysis to comprehensively explore the dimensions and attributes of RCS as it pertains to allied and public health professionals in LMICs, propose empirical referents and suggest an operational definition. Ovid MEDLINE, Embase, CINAHL and Cochrane CENTRAL were searched from inception to 27 July 2023, to identify studies on RCS in LMICs. The Walker and Avant approach to concept analysis was selected because it provides a framework for systematically examining and clarifying the meaning and implications of RCS. This method involves a structured process of defining RCS, identifying its attributes, antecedents, consequences and cases, and ultimately providing a clear understanding of its meaning and implications. Identifying empirical referents offers measurable indicators that researchers and policymakers can use to assess the effectiveness of RCS initiatives in LMICs. RCS for health professionals in LMICs involves a sustainable process that equips them with essential research skills, fostering the ability to conduct high-quality research and improve healthcare delivery in resource-constrained settings. RCS aims to empower health professionals to apply evidence-based practices, reduce disparities and enhance the well-being of populations in LMICs. Ultimately, a concept analysis of RCS empowers us to harness the full potential of research to enhance healthcare delivery, improve patient outcomes and advance the well-being of populations worldwide.

Use of ChatGPT for education by engineering students in developing countries: a mixed-methods study

ABSTRACT Developing countries face challenges in AI integration into learning initiatives. With the widespread use of ChatGPT, many concerns were expressed. Thus, it is crucial to investigate students' attitudes toward ChatGPT and the factors influencing their decision to continue using it in the future. We used a mixed-methods triangulation design based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and collected data based on convenience sampling from N = 195 engineering students in developing countries through semi-structured surveys with open-ended questions. Quantitative analysis included descriptive statistics and logistic regression, while thematic analysis was used for the qualitative part. Most students (89.69%) use ChatGPT, with all the elements of the UTAUT framework being strong predictors of their intention to continue. Most have continuous internet access and feel comfortable using technology. High-frequency usage, perceived benefits, and peer encouragement positively influence students' intention to continue using ChatGPT. However, concerns about accuracy, privacy, and laziness negatively correlate with usage intention. Address personal, institutional, and governmental concerns to integrate ChatGPT safely in educational systems, ensuring equitable access and preparing for future e-learning initiatives.

Correlations of Physical and Psychological Health in Parents of Individuals With Autism Spectrum Disorder.

Individuals with autism spectrum disorder (ASD) have social communication difficulties and restricted, repetitive, and/or sensory behaviors or interests. The prevalence of ASD is now 1 in 36 individuals. Parents of individuals with ASD face challenges that can affect their physical and psychological well-being. With the long-term goal to tailor an exercise program, the purpose of this study was 2-fold: (1) establish the baseline physical and mental health of parents of individuals with ASD and (2) estimate the relationship of physiologic variables with psychological variables of health for parents of individuals with ASD. This descriptive, cross-sectional study (N = 44) explored physical health measures and the correlation between physical and psychological health, using measures of anxiety, stress, parenting depression, and positive thinking for parents who care for individuals with ASD. The common characteristics that these parents shared was high body fat and low physical activity. Body fat was negatively correlated to total step count (r = -0.428, P < .05), grip strength (r = -0.319, P < .5), and total distance walked in the week (r = -0.661, P < .01), and positively correlated to 5-times sit to stand (r = 0.337, P < .05). Low activity correlated to increased parenting stress of advocating for child's needs (r = -0.310, P = .043). Understanding relationships between physical and psychological health informs effective interventions and support systems for parents. Parents need supports to be able to prioritize exercise. Future studies should include a larger sample to verify these effects.

Transforming Screening, Risk Stratification, and Treatment Optimization in Chronic Liver Disease Through Data Science and translational Innovation

Background: Chronic liver diseases continue to face challenges in prognosis, treatment selection, disease mechanisms, screening, and therapeutic optimization. Promising innovations could address these gaps through data integration and novel analytic approaches.Main Body: MAPS-CRAFITY integrating clinical variables, AFP, and CT/MRI findings, and transformer modeling of RFA data improve HCC outcome prediction to guide management. Analyses revealing IL21R as a PBC susceptibility gene and implicating dysfunctional VWF processing in portal hypertension deliver mechanistic insights. Quantifying childhood MAFLD informs screening needs, while supporting use of G6PD deficient liver donors enables transplantation access expansion through risk stratification. Updating Baveno criteria enhances PBC prognosis, and an HCC prognostic score identifies optimal RFA candidates to maximize treatment efficacy.Conclusion: Recent research leverages diverse data types, genetics, imaging, and machine learning to develop integrated predictive systems that allow more personalized therapy selection. Elucidating molecular pathways provides therapeutic targets and prognostic biomarkers. Evidence-based screening and risk models facilitate delivering tailored interventions. Optimization of current modalities through prognostic validation and patient selection improves real-world effectiveness. Multifaceted modern research approaches promise to address unmet needs and transform hepatology care.

Unsociability and social adjustment in Chinese preschool migrant children: the moderating role of receptive vocabulary

Peer relationships play an indispensable role in the social, emotional, and cognitive development of children. However, children exhibiting social withdrawal, such as unsociability, may face challenges in social adjustment. In collectivistic cultures like China, unsociability may be perceived negatively, aligning poorly with collective norms. The objective of the present investigation was to examine the associations between unsociability, receptive vocabulary, and indicators of social adjustment in a cohort of young migrant children residing in urban regions of mainland China. The study mainly aimed to investigate the potential moderating influence of receptive language on these associations. The study involved 148 young children (82 boys, 66 girls, Mage = 62.32 months, SD = 6.76) enrolled in preschools or kindergartens in Shanghai, People’s Republic of China. Multiple sources of assessment were utilized, encompassing evaluations from mothers (about child unsociability), teacher (assessing social adjustment), and standardized tests (measuring receptive vocabulary). The results indicated that the relations between unsociability and peer exclusion were more positive among children with lower levels of receptive vocabulary but not significant for children with higher levels of receptive vocabulary. Similarly, the relations between unsociability and peer exclusion were more negative among children with lower levels of receptive vocabulary but not significant for children with higher levels of receptive vocabulary. Thus, this study informs us about how receptive vocabulary is jointly associated with unsociable children’s development. As well, the findings highlight the importance of considering the meaning and implication of unsociability in Chinese culture.

Integrated Hfq-interacting RNAome and transcriptomic analysis reveals complex regulatory networks of nitrogen fixation in root-associated Pseudomonas stutzeri A1501.

Numerous experimental approaches often face challenges in distinguishing between direct and indirect effects of Hfq-mediated regulation. New technologies based on high-throughput sequencing are increasingly providing insight into the global regulation of Hfq in gene expression. Here, enhanced UV cross-linking immunoprecipitation coupled with high-throughput sequencing was employed to identify the Hfq-binding sites and potential targets in the root-associated Pseudomonas stutzeri A1501 and identify hundreds of novel Hfq-binding RNAs that are predicted to be involved in metabolism, environmental adaptation, and nitrogen fixation. In particular, we have shown Hfq interactions with various regulatory proteins' mRNA and their potential targets at the posttranscriptional level. This study not only enhances our understanding of Hfq regulation but, importantly, also provides a framework for addressing integrated regulatory network underlying root-associated nitrogen fixation.

Microalgae detection based on improved YOLOv5

AbstractAccurate detection of algae in microscopic image plays a crucial role in water quality monitoring. However, the existing object detection methods still face challenges in accurately detecting different categories of algae in microscopic image. In order to improve the accuracy, an improved YOLOv5s model is proposed for microalgae detection, by combining a Receptive Field Enhancement (RFE) module, the Wise‐IoU v3 dynamic non‐monotonic focal loss function, and a Dynamic head (Dyhead), which is termed receptive field enhancement wise‐IoU dyhead (RWD)‐you only look once (YOLO). Firstly, to detect microalgae of various scales, the Bottleneck in the C3 module of YOLOv5s is replaced with a more reasonable RFE module. Secondly, Wise‐IoU v3 is applied to enhance detection accuracy by assigning varying weights between high‐quality and low‐quality images. Finally, Dyhead is introduced to enhance the representation capacity of the detection head by integrating three attention mechanisms: scale awareness, spatial awareness, and task awareness. The proposed RWD‐YOLO model significantly enhances the accuracy of algae detection in microscopic image. Specifically, the experimental results on the microalgae dataset show that the RWD‐YOLO achieves an mAP@0.5 of 93.2% and an mAP@0.5:0.95 of 65.1%. Compared to the original YOLOv5s, mAP@0.5 and mAP@0.5:0.95 are improved by 3.7% and 5.7%, respectively.

Cultural Parallels and Unique Features Kyrgyz and Native Americans: Comparative Analysis

This paper examines the cultural parallels and unique features of Kyrgyz people and Native Americans, shedding light on the remarkable similarities and differences that define these two distinct indigenous groups. Using an interdisciplinary approach, this study examines the historical, social, and cultural aspects of both Native Americans and Kyrgyz, seeking to unravel the complexity of their traditions, beliefs, and practices. The study reveals striking parallels between spiritual beliefs and reverence for nature that are deeply rooted in both cultures. The symbolic significance of animals, the spiritual connection to the earth, and the practice of traditional healing techniques reflect a shared appreciation of the natural world and a harmonious relationship with the environment. Moreover, oral traditions and stories from both groups serve as vital channels for preserving cultural heritage and passing ancestral wisdom from one generation to the next. On the other hand, the unique traits of each culture are revealed through the study of their artistic expressions, linguistic diversity and social structures. The nomadic heritage of the Kyrgyz has shaped their customs and folklore, while the diverse linguistic traditions and artistic skills of Native American tribes demonstrate the richness of their cultural traditions. In addition, the impact of historical and contemporary influences on both groups is examined to elucidate the resilience and adaptation of their cultural identities. The enduring legacy of colonialism and the persistence of indigenous knowledge in the face of contemporary challenges provide a critical backdrop for understanding the dynamic nature of Native American and Kyrgyz cultures. By contrasting these cultural characteristics, this comparative analysis aims to foster a deeper understanding of the interconnectedness of global indigenous communities while respecting the distinctiveness of their heritage. Ultimately, this study aims to stimulate intercultural dialogue and promote mutual understanding by highlighting the richness of human diversity and the enduring spirit of resilience of indigenous peoples.

Integrating Omics Approaches for Climate-Resilient Crops: A Comprehensive Review

Climate change is a looming threat to global agriculture, impacting temperature, rainfall patterns, pest dynamics, and soil quality. These challenges transcend numerous crops vital for global food security. Drought, soil acidity, and nutrient fluctuations induced by climate change impede crop productivity, necessitating the development of breeding strategies to produce climate-resilient varieties. This review delves into the integration of omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, to bolster breeding programs across diverse crops. By harnessing high-throughput technologies, researchers gain insights into the genetic and molecular mechanisms underlying traits such as stress resistance, yield, and disease tolerance. The cultivation of elite cultivars with enhanced stress tolerance is paramount for sustainable agriculture in the face of climate change. Various breeding approaches, encompassing functional genomics and mutagenomics, are explored alongside the application of genome editing tools like CRISPR/Cas9 and TALEN for targeted trait enhancement. Through the integration of multi-omics data, novel genetic targets are unearthed, facilitating the development of crop varieties resilient to climate-induced stressors beyond maize. This review underscores the significance of multi-omics in crop breeding and highlights strides made toward climate-resilient crop production. Understanding crop responses to abiotic stresses induced by climate change is imperative for the development of resilient varieties. The integration of modern genetics into classical breeding methods aims to cultivate stress-resistant cultivars, mitigating food security risks. Multi-omics approaches play pivotal roles in unraveling crop performance and stress tolerance mechanisms under diverse environmental conditions. Moving forward, the integration of multi-omics approaches will pinpoint candidate genes and pathways, enabling precision breeding to enhance crop performance amidst changing climates. These endeavors will propel the advancement of climate-resilient crops, safeguarding global food security in the face of climate change's challenges.

Export diversification dimensions and performance: Analysis and industrial policy insights from Italian territories over Covid-19 shocks

Export diversification has been long discussed as a strategy to shield from external shocks and stabilize export levels. At the same time, it can proxy for the presence of specific productive and geoeconomic capabilities. This paper considers geographical and sectoral diversification of industrial exports proposing HHI-based indexes that consider different levels of aggregation. Specifically, we explore how these metrics are associated with each other, and how this association is moderated by different levels of export intensity and stability. Overall, they both explain well variations in export intensity over the COVID-19 asymmetric shocks. Further, exposure toward EU markets shows a positive association with stability. These findings and the heterogeneity lens used are then interpreted stressing the relevance of place-based policies in guiding export diversification strategies in the face of global economic challenges.

Influence of Leadership Competencies on Implementation of Operational Strategies in Organizations in Kenya: A Case of Geothermal Development Company.

Leadership played a pivotal role in shaping organizational direction and strategy execution, especially in the face of challenges posed by dynamic environments and a diverse workforce. The study explored the influence of leadership competencies on the implementation of operational strategies within the Geothermal Development Company (GDC) in Kenya. Drawing upon various theoretical frameworks including Path-Goal Theory, Great Man Theory, Leadership-Member Exchange (LMX) Theory, and Trait Theory, the research delved into the cognitive, emotional, social, and functional competencies of leaders and their impact on strategy realization. The study, employing a descriptive research design, collected data from 78 management staff members of GDC through structured questionnaires. Findings revealed significant positive correlations between leadership competencies and the implementation of operational strategies. Specifically, cognitive competencies, encompassing problem-solving and analytical skills, were found to strongly influence strategy implementation. Emotional competencies, such as self-awareness and relationship management, also played a significant role in fostering a conducive environment for strategy execution. Social competencies, including interpersonal skills and teamwork, positively impacted the coordination and cooperation necessary for successful strategy implementation. Additionally, functional competencies, comprising communication and decision-making abilities, were identified as crucial elements in aligning resources and guiding organizational efforts towards strategic objectives. The regression analysis further validated the significance of leadership competencies in predicting the implementation of operational strategies. Cognitive, emotional, social, and functional competencies collectively explained 61.8% of the variance in strategy implementation within GDC. The study underscored the importance of developing multifaceted leadership competencies tailored to the unique contexts of organizations, especially in the public sector where challenges such as limited resources and diverse roles prevailed. These findings contributed to the existing body of knowledge on leadership and strategy implementation, particularly in the context of public entities like GDC. Practical implications suggested that organizations should invest in leadership development programs that focus on enhancing cognitive, emotional, social, and functional competencies among their leaders to drive successful strategy execution. By understanding and leveraging these competencies, organizations could navigate complexities, overcome barriers, and achieve their strategic objectives effectively.

3D Printed MXene-Based Wire Strain Sensors with Enhanced Sensitivity and Anisotropy.

Stretchable strain sensors play a crucial role in intelligent wearable systems, serving as the interface between humans and environment by translating mechanical strains into electrical signals. Traditional fiber strain sensors with intrinsic uniform axial strain distribution face challenges in achieving high sensitivity and anisotropy. Moreover, existing micro/nano-structure designs often compromise stretchability and durability. To address these challenges, a novel approach of using 3D printing to fabricate MXene-based flexible sensors with tunable micro and macrostructures. Poly(tetrafluoroethylene) (PTFE) as a pore-inducing agent is added into 3D printable inksto achieve controllable microstructural modifications. In addition to microstructure tuning, 3D printing is employedfor macrostructural design modifications, guided by finite element modeling (FEM) simulations. As a result, the 3D printed sensors exhibit heightened sensitivity and anisotropy, making them suitable for tracking static and dynamic displacement changes. The proposed approach presents an efficient and economically viable solution for standardized large-scale production of advanced wire strain sensors.

One-Dimensional Crystal-Structure Te-Se Alloy for Flexible Shortwave Infrared Photodetector and Imaging.

Flexible shortwave infrared detectors play a crucial role in wearable devices, bioimaging, automatic control, etc. Commercial shortwave infrared detectors face challenges in achieving flexibility due to the high fabrication temperature and rigid material properties. Herein, we develop a high-performance flexible Te0.7Se0.3 photodetector, resulting from the unique 1D crystal structure and small elastic modulus of Te-Se alloying. The flexible photodetector exhibits a broad-spectrum response ranging from 365 to 1650 nm, a fast response time of 6 μs, a broad linear dynamic range of 76 dB, and a specific detectivity of 4.8 × 1010 Jones at room temperature. The responsivity of the flexible detector remains at 93% of its initial value after bending with a small curvature of 3 mm. Based on the optimized flexible detector, we demonstrate its application in shortwave infrared imaging. These results showcase the great potential of Te0.7Se0.3 photodetectors for flexible electronics.

Agronomic drivers of pesticide use in small-scale horticultural systems in central Mexico: cropping and farming system factors.

Abstract Horticultural Production Systems (HPS) in Mexico face challenges due to small-scale operations, limited resources, and high dependence on family labor. This study explores the use of agrochemicals in HPS and its impact on productivity and potential exposure to pesticides. Through on-farm surveys in the Morelia-Queréndaro valley, Central Mexico, factors influencing agrochemical use and toxicity were investigated. Results show that HPS configuration plays a pivotal role in predicting agrochemical use. HPS dominated by a single crop tend to use more herbicides and fertilizers, while diversified systems use fewer herbicides. Crop-specific management practices, such as row spacing and intercropping, significantly influence herbicide usage. Surprisingly, higher volumes of insecticides and fungicides do not consistently correlate with increased yields. Additionally, relationships between pesticide use and crop yields vary across onion cropping systems, emphasizing the need for tailored management strategies. We highlight the significant toxicity of insecticides and the importance of understanding factors determining their application volumes. Overall, this research underscores the complexity of agrochemical use in HPS and emphasizes the potential of diversified farming systems to reduce reliance on agrochemical inputs while maintaining productivity. These findings contribute to a deeper understanding of sustainable agriculture practices and provide valuable insights for policy makers and farm managers.

Policy brief: Polish LGBTQIA+ students at risk: How can schools protect them?

Recognising and meeting the social and emotional wellbeing needs of LGBTQIA+ students is an essential education policy issue globally. Yet, research suggests that this vulnerable group continues to face challenges to their ability to feel culturally safe at school. Negative experiences include verbal and physical abuse, and this often results in poor outcomes for students. Certain European countries such as Malta and The Netherlands have demonstrated positive progress towards enacting inclusive policy, while others, including Poland, are known to have made little or no development in this area. This paper provides a policy issue analysis on the current situation in Polish schools while considering the added threat of LGBT+ free zones that have plagued the political landscape and exist as a further barrier to tolerance and empowerment. Following this discourse, recommendations for school communities have been provided for the purpose of establishing safe learning environments for LGBTQIA+ students.

Fringe-based depth segmentation via minimum-fringe-period-based singular points extraction

In the field of machine vision, depth segmentation plays a crucial role in dividing targets into different regions based on abrupt changes in depth. Phase-shifting depth segmentation is a technique that extracts singular points to form segmentation lines by leveraging the phase-shifting invariance of singular points in different wrapped phase maps. This makes it immune to color, texture, and camera exposure. However, current phase-shifting depth segmentation techniques face challenges in the precision of segmentation. To overcome this issue, this paper proposes a singular points extraction technique by constructing a more comprehensive threshold with the help of the minimum period of the phase map. Taking full advantage of the proposed technique, mean-value points and order singular points are accurately filtered out, and the integrity of segmentation lines in high-curvature regions can be guaranteed. During optimization processing, the precision of segmentation is improved by employing a low-cost morphology-based optimization model. Simulation results demonstrate the segmentation accuracy reaches up to 98.58% even in a noisy condition. Experimental results on different objects indicate that the proposed method exhibits good generalization and robustness.

Next‐generation energy‐efficient optical networking: DQ‐RGK algorithm for dynamic quality of service and adaptive resource allocation

SummaryIn green optical networking, designing an adaptive energy‐saving scheme plays a vital role, in optimizing energy consumption by dynamically adjusting resources based on network traffic and environmental conditions, to a more sustainable and efficient optical communication infrastructure. Traditional methods in optical networking face challenges such as static resource allocation, limited adaptability, inefficient power usage, environmental insensitivity, and scalability issues. Therefore this article proposed a novel method named Dynamic Quality of Service based Random update Genghis Khan (DQ‐RGK) algorithm, the proposed model can tackle the abovementioned complexities. In this study, cluster head dynamic placement is utilized to optimize the network's performance by adapting the placement of cluster heads to the current topology, load distribution, and energy levels in the network nodes. Additionally, Dynamic Quality of Service (QoS) is employed to respond dynamically to changes in network conditions, adapting to varying traffic patterns and resource availability. In this work, the Genghis Khan Shark optimization with a random update strategy is implemented for hyperparameter optimization to enhance the performance of the DQ‐RGK method. The DQ‐RGK adjusts the parameters of QoS in real‐time, and this ensures that network resources based on the requirements changed and priorities of applications, which ultimately optimizes performance and enhances user experience. By dynamically assigning and reallocating resources based on the current demand the algorithm enhances overall network efficiency and reduces energy consumption. Then, this work analyzes the experimental results, where some evaluation measures estimate the DQ‐RGK method's performance. Routing efficiency, latency, scalability, spectral efficiency, Packet Delivery Ratio, throughput, network lifetime, energy consumption, jitter, and energy consumption are the measures employed by the DQ‐RGK model. In The results, other routing models that do not provide efficiency are utilized, a comparison of these other routing models is represented in results. The overall DQ‐RGK model's effectiveness is represented in the experimental results and its effectiveness is greater among other methods.

Analysis and Design of Water Distribution Network for Jabalpur Cantonment Board Area

In this research paper focuses on studying and improving the water distribution network in the Jabalpur Cantonment Board Area. Water distribution networks are crucial infrastructures for ensuring reliable water supply to communities. However, many areas, including Jabalpur Cantonment, face challenges related to water distribution efficiency, reliability, and equitable access. The study begins with a comprehensive analysis of the existing water distribution network in the Jabalpur Cantonment Board Area. Factors such as network layout, pipe material, age of infrastructure, and water demand patterns are thoroughly examined to identify existing inefficiencies and areas for improvement. Using advanced engineering tools such as WaterGems and methodologies, an optimized design for the water distribution network is proposed. This design considers factors such as hydraulic efficiency, pressure management, and resilience to minimize water losses and ensure consistent water supply to consumers. Furthermore, the study incorporates considerations for future growth and development in the Jabalpur Cantonment Board Area. By employing sustainable design practices and incorporating modern technologies, the proposed water distribution network aims to meet the present and future water needs of the community while minimizing environmental impact. By implementing the proposed design improvements, the Jabalpur Cantonment Board can achieve a more sustainable, efficient, and reliable water supply network, ultimately improving the quality of life for its residents.

N-doped 3D carbon encapsulating nickel selenide nanoarchitecture with cation defect engineering: An ultrafast and long-life anode for sodium-ion batteries

Transition metal chalcogenides (TMCs) hold great potential for sodium-ion batteries (SIBs) owing to their multielectron conversion reactions, yet face challenges of poor intrinsic conductivity, sluggish diffusion kinetics, severe phase transitions, and structural collapse during cycling. Herein, a self-templating strategy is proposed for the synthesis of a class of metal cobalt-doped NiSe nanoparticles confined within three-dimensional (3D) N-doped macroporous carbon matrix nanohybrids (Co-NiSe/NMC). The cation defect engineering within the developed Co-NiSe and 3D N-doped carbon plays a crucial role in enhancing intrinsic conductivity, reinforcing structural stability, and reducing the barrier to sodium ion diffusion, which are verified by a series of electrochemical kinetic analyses and density functional theory calculations. Significantly, such cation defect engineering not only reduces overpotential but also accelerates conversion reaction kinetics, ensuring both exceptional high-rate capability and extended durability. Consequently, the optimally engineered Co-NiSe/NMC demonstrates a remarkable rate performance, delivering 390 mAh g−1 at 10 A g−1. Moreover, it exhibits an unprecedented lifespan, maintaining a remarkable capacity of 403 mAh g−1 after 1400 cycles and 318 mAh g−1 after 4000 cycles, even at high rates of 1.0 and 2.0 A g−1, respectively. This work marks a substantial advancement in achieving both high performance and prolonged cycle life in sodium-ion batteries.

Ambient conditions of the operating theatre and its correlation with fatigue and sleep quality of operating room workers: a cross-sectional survey

BackgroundAnesthesia providers face numerous occupational hazards, including exposure to anesthesia gases, which can lead to fatigue. These professionals face challenges such as night shifts, OR stress, limited mobility and sunlight access, high workload, inadequate rest breaks. Health-related sociodemographic variables, such as smoking, sleep patterns, and obesity. Our research aims to explore various risk factors associated with fatigue among operating theatre workers including sleep quality.MethodsA cross-sectional study was conducted on 227 of operating room healthcare professionals from five tertiary hospitals in Saudi Arabia, for a period of 6 months, between January 1, 2023 to June 1, 2023. The study used a five-point Likert scale sheet and the FSS “fatigue severity scale” to analyze and measure fatigue and sleep quality. The questionnaire included all socio-demographic variables, work conditions, and fatigue severity scale items.ResultsThe major findings revealed a significant correlation between fatigue severity scores and exposure to anesthesia gases. Socio-demographic variables such as smoking have showed major relevance to fatigue in the sample size, as (76.6%) of the participants that answered as regular smokers have showed result of positive correlation to fatigue and with a significant of (0.034). Out of the total sample, 76.1% were exposed to anesthesia gases once daily, showing a positive association with fatigue severity scores. Work-related factors like job experience and position also had a lower association with fatigue severity. p (0.031) Univariate logistic regression p (0.035).ConclusionThe study found that the work-related conditions like workload on Anesthesia technicians and technologists over 44 h per week and gas exposure is directly linked to fatigue severity and sleep quality so is the socio-demographic considerations. With poor sleep quality in younger staff which is documented in the study result a large-scale prospective analysis to understand the factors affecting OR staff’s sleep quality and fatigue severity and what can be done to regulate working hours and break time and incorporate naps in to enhance patient safety and well-being for anesthesia providers in Saudi Arabia.