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Abstract Background Insomnia is a prevalent sleep disorder affecting cognitive functions critical to academic performance. University students, particularly in high-stress academic settings, are highly vulnerable. Despite its significant impact on students' health and education, there is limited research on the prevalence of insomnia among university students in Saudi Arabia. This systematic review and meta-analysis aim to assess the prevalence of insomnia among university students in Saudi Arabia, focusing on demographic variations and academic settings, to provide evidence for targeted interventions. Methods A comprehensive literature search was conducted across databases including PubMed, Scopus, and Web of Science, with additional manual searches. Inclusion criteria were cross-sectional studies addressing insomnia prevalence among Saudi university students, using standard diagnostic criteria. A total of 11 studies met the inclusion criteria, comprising data from diverse faculties, including medical and non-medical disciplines. Quality assessment was conducted using the Newcastle-Ottawa Scale. Statistical analyses were performed using a random-effects model to account for heterogeneity. Results Eleven studies, involving a total of 8297 university students, were included in the analysis. Insomnia prevalence varied widely, ranging from 19.3% to 98.7%, with a pooled prevalence of 43.3% (95% CI 28.9–58.2%). Subgroup analyses showed a prevalence of 38.6% among medical students and 38.7% among female students. The analysis revealed high heterogeneity (I 2 = 99.17%), indicating significant variability in study designs, populations, and diagnostic methods. Conclusions Insomnia is highly prevalent among university students in Saudi Arabia, with significant variations across demographics and academic contexts. The findings underscore the urgent need for targeted interventions, including stress management, improved sleep hygiene education, and support systems to mitigate the impact of insomnia on academic performance and overall health. Future research should explore the longitudinal impacts of insomnia and the efficacy of tailored interventions in this population.

Orthopaedic trauma is a predominant cause of patient mortality and prompt surgical interventions. The locking compression plate (LCP) is widely regarded as a gold standard in treating bone fractures. However, current fixation materials, such as 316 L stainless steel (316 L SS) and titanium (Ti) alloys induce stress shielding. A novel design approach is considered to design the next generation of bone plates to minimize stress shielding through design for additive manufacturing principles. Embedding of 316 L SS sheets within the bone plate structure has improved the mechanical properties by 200% compared with PLA-only plate, resulting in a flexural modulus of 9.3 GPa, which is closer to the cortical bone range of 10–25 GPa. In contrast, commercial plates measured 51 GPa for Ti and 112 GPa for 316 L SS. The novel plates showed to have a lower economic and environmental impact than commercial ones. Additively manufactured bone plates are more sustainable and cost-effective than current commercial ones.

Introduction: In diabetes mellitus (DM) patients, obtaining a good night’s sleep is crucial for maintaining body caloric intake, controlling insulin levels, and reducing the likelihood of engaging in unhealthy behavior. Patients with poor sleep quality may experience impaired glycemia, playing a significant role in the development of chronic complications. This study aims to explore the effects of DM complications on sleep quality among Saudi Arabian patients. Patient and Methods: This is a cross-sectional study conducted among patients with diabetes. A self-administered, validated questionnaire translated into Arabic was distributed among diabetic patients using an online survey. The questionnaire includes sociodemographic characteristics (i.e. age, gender, marital status, etc.), the medical history of the patients, and a questionnaire about sleep quality. Results: Out of 4171 patients involved, 52.7% were females and 27.7% were aged between 40 and 60 years old. The prevalence of patients with perceived poor sleep quality was 24.1%. Significant predictors of poor sleep quality were the gender female, having social stressors, comorbid sleep disorders, associated comorbidities, increasing HbA1c levels, being overweight/obese, and diabetes complications. Furthermore, sleep disturbance, taking sleep medications, daytime sleepiness, and having bad dreams during sleep were also identified as prognostic factors for poor sleep quality. Conclusion: The subjective poor sleep quality of patients with diabetes was 24.1%. Poor sleep quality was significantly demonstrated by females who were having social stressors, comorbid sleep disorders, comorbidities, uncontrolled HbA1c levels, elevated BMI levels, and complications of diabetes. However, regular physical activity and adequate sleep were estimated to be the protective factors against poor sleep quality. Further research is needed to establish the effect of sleep quality among patients with DM.

This study investigated the incorporation of desized short recycled carbon fiber (rCF) into polylactic acid (PLA) matrix for fused deposition modeling (FDM) printing. Composite filaments were produced by ball milling mixing and then melt extrusion, unlike the majority of the existing studies, which employed multi-cycle compounding/extrusion. Composite filaments with different loadings of rCF were produced. Tensile testing was carried out to evaluate the influence of rCF on mechanical properties. The morphology of the extruded filaments, as-printed, and fractured samples was assessed through scanning electron microscopy (SEM). The thermal properties of the produced filaments were also evaluated using differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The SEM images demonstrated a homogeneous distribution of the rCF within the PLA matrix, with good adhesion between PLA and desized rCF. DSC showed lesser thermal alteration in the pure PLA filaments compared to PLA pellets due to the currently used mixing methodology. TGA results showed enhanced thermal stability with adding rCF into PLA. Incorporation of rCF increased tensile modulus up to 58.30 % compared to pure PLA. The tensile modulus of the PLA/15 %rCF composite was higher than that of the commercially available PLA/15 %vCF composite (19.64 % enhancement) while showing similar strength. In fractured specimens, the intra-layer failure mechanism was dominated, while no significant interlayer separation was observed. The study demonstrates the potential of employing eco-friendly desized rCF as a substitute for vCF in producing fiber-reinforced PLA for FDM printing.

Abstract Background It is hypothesized that whole salivary prostaglandin E2 (PgE2) levels are higher in patients with type-2 diabetes mellitus (type-2 DM) than non-diabetic individuals with periodontal inflammation; and that whole salivary expression of PgE2 is correlated with hemoglobin A1C (HbA1c) levels. The aim of the present study was to compare whole salivary PgE2 levels among patients with type-2 DM and non-diabetic individuals with periodontal inflammation. Methods Sociodemographic data, duration since the diagnosis and management of type-2 DM, most recent hemoglobin A1C (HbA1c level), and any familial history of DM was retrieved from patient’s healthcare records. Participants were divided into four groups: Group-1: type-2 diabetics with periodontal inflammation; Group-2: type-2 diabetics without periodontal inflammation; Group-3: non-diabetics with periodontal inflammation; and Group-4: non-diabetics without periodontal inflammation. Plaque and gingival indices (PI and GI), probing depth (PD), clinical attachment loss (CAL) and marginal bone loss (MBL) were measured. Unstimulated whole saliva samples were collected and PgE2 levels were measured. Group-comparisons were done and P

Abstract Background Periodontal phenotype is regarded to be one of the key factors influencing the efficacy of restorative therapies in dental practice. The objective of the systematic review was to explore the importance of thin and thick periodontal phenotypes and how they affect the outcome of periodontal and restorative therapies by looking at a number of academic publications from various online databases. Methods Following the PRISMA guidelines (Preferred Reporting Items for Systematic Review standards), relevant data will be searched and retrieved from three significant scientific databases, including PubMed, EBSCO, and Scopus. The articles with full texts that matched the keywords and published in English between 2018 and 2023 were taken into consideration. Results The majorities of these articles were based on the type of periodontal phenotype and their impact on periodontal and restorative treatment outcomes were selected. The initial search yielded a total of 530 articles. Only 273 were relevant to the review’s objectives, and these were considered for determining eligibility. Only 20 publications were eligible for analysis. Conclusion Understanding these anatomical aspects of periodontal phenotype is crucial to both periodontology and restorative dentistry. The clinical outcome of restorative, prosthetic, orthodontic, surgical, and periodontal therapies is determined in large part by the periodontal phenotype, which also plays a significant role in clinical failure or success in dental treatments. Trial registration This study protocol registered with the International Prospective Register of Systematic Reviews (PROSPERO) dated 16th June 2023 with the registration ID CRD42023432568.

Mahdi Mutahar,1 Nasser M Al Ahmari,2 Thrya S Gadah,2 Mohammed Ali Mohammed Kariri,3 Hana Y Madkhli,3 Dawood M Somaili,4 Yahya MY Mobarki,5 Omar Ahmed Darraj,6 Sultan M Halawi,7 Mohammed M Al Moaleem8 1Dental Academy, University of Portsmouth, Portsmouth, PO1 2QG, UK; 2Prosthetic Department, College of Dentistry, King Khalid University, Abha, 62529, Saudi Arabia; 3Dental Department, Samtah General Hospital, Ministry of Health, Jazan, Saudi Arabia; 4Dental Department, Dayhamah Primary Health Center, Ministry of Health, Jazan, Saudi Arabia; 5Dental Department, Aldureah Primary Health Center, Ministry of Health, Jazan, Saudi Arabia; 6Dental Department, Algahw Primary Health Center, Ministry of Health, Jazan, Saudi Arabia; 7Dental Department, Al Raha Primary Health Center, Ministry of Health, Jazan, Saudi Arabia; 8Department of Prosthetic Dental Science, College of Dentistry, Jazan University, Jazan, 45142, Saudi ArabiaCorrespondence: Mahdi Mutahar; Mohammed M Al Moaleem, Department of Prosthetic Dental Science, College of Dentistry, Jazan University, Jazan, 45142, Saudi Arabia, Tel +966-550599553, Email mahdi.mutahar@port.ac.uk; malmoaleem@jazanu.edu.saAim: To investigate the hardness and energy absorption of four commercially available chairside types of silicone materials and compare their properties with heat-cured silicone material.Materials: The chairside materials investigated were GC reline soft, mucopren soft, sofreliner soft and elite soft relining. The heat-cured polymer silicone material was Molloplast B. All soft lining materials were processed according to manufacturers’ instructions. Two properties were investigated. Ten specimens for each test were prepared for each soft liner except for the water absorption and solubility test, for which only five specimens were prepared. The specimens of energy absorption (10 × 10 × 3 mm) were tested using a Lloyd instruments testing machine. Hardness specimens (38 × 38 × 3) were tested using a shore A durometer and were divided into two subgroups; dry and wet storage.Results: The specimens of energy absorption (10 × 10 × 3 mm) were tested using a Lloyd instruments testing machine. Sofreliner soft was significantly softer than Molloplast B. GC reline soft was significantly harder than molloplast B. At high loads, sofreliner soft and elite soft relining was significantly more resilient than molloplast B. Mucopren soft was significantly stiffer than Molloplast B. At low loads, all materials showed similarities in stiffness and resilience; the difference between them was insignificant. After one month of immersion, GC reline and mucopren significantly increased hardness values.Conclusion: In all conditions and at all four-time points, the hardness values for GC Reline soft were the greatest, and hardness values for Sofreliner Soft were the least. Some chairside soft denture lining materials could have similar significant properties to molloplast-B, such as sofreliner soft and elite.Keywords: complete dentures, denture liners, hardness, polyvinyl siloxane liner, resilience, energy absorption, soft denture lining materials, stiffness

The rapid advancement of additive manufacturing (AM) requires researchers to keep up with these advancements by continually improving the AM processes. Improving manufacturing processes involves evaluating the process outputs and their conformity to the required specifications. Process capability indices, calculated using critical quality characteristics (QCs), have long been used in the evaluation process due to their proven effectiveness. AM processes typically involve multi-correlated critical QCs, indicating the need to develop a multivariate process capability index (MPCI) rather than a univariate capability index, which may lead to misleading results. In this regard, this study proposes a general methodological framework for evaluating AM processes using MPCI. The proposed framework starts by identifying the AM process and product design. Fused Deposition Modeling (FDM) is chosen for this investigation. Then, the specification limits associated with critical QCs are established. To ensure that the MPCI assumptions are met, the critical QCs data are examined for normality, stability, and correlation. Additionally, the MPCI is estimated by simulating a large sample using the properties of the collected QCs data and determining the percent of nonconforming (PNC). Furthermore, the FDM process and its capable tolerance limits are then assessed using the proposed MPCI. Finally, the study presents a sensitivity analysis of the FDM process and suggestions for improvement based on the analysis of assignable causes of variation. The results revealed that the considered process mean is shifted for all QCs, and the most variation is associated with part diameter data. Moreover, the process data are not normally distributed, and the proposed transformation algorithm performs well in reducing data skewness. Also, the performance of the FDM process according to different designations of specification limits was estimated. The results showed that the FDM process is incapable of different designs except with very coarse specifications.

BACKGROUND: The objective of this study was to investigate the use of mind maps as an active teaching strategy to enhance critical thinking skills (CTSs) among respiratory therapy (RT) students in Saudi Arabia. MATERIALS AND METHODS: A total of 86 participants from two RT programs in Saudi Arabian Universities, King Saud bin Abdulaziz University for Health Sciences and The Batterjie Medical College, were randomly assigned to either the mind map group (MMG) or the standard note-taking group (SNTG). With the quasi-experimental design and quantitative method, mean comparisons were made between the groups using an independent t-test. RESULTS: There was no significant change between the pre-SNTG and post-SNTG as measured by the health sciences reasoning test (HSRT) after 15 weeks of standard note-taking (SNT). However, it showed the difference between the pre-MMG and post-MMG (P = .02) as measured by the HSRT after 15 weeks of intervention. There was also a significant change between the post-MMG and SNTG (P = .04) as measured by the HSRT, where the MMG had higher scores. However, the study had limitations, which conceded to the failure of participants in the test and the subjectivity of respondents where they were excluded from the study; also, for generalizability of the result, the study should have been taken beyond Riyadh and Jeddah. CONCLUSION: Prior to this study, the effectiveness of mind mapping (MM) in the respiratory discipline has not yet been explored. It found that mind mapping was effective at improving CTS, while SNT was not, as measured by pre- and post-test HSRT scores. This was the first investigation into MM’s impact on CTS within respiratory therapy education.

Artificial Intelligence (AI) technologies are gradually becoming widespread in pediatric orthopedic surgery and contribute to diagnostic and surgical processes, planning, execution, and treatment. This review focuses on new AI technologies that enhance bone age determinations and identification of early musculoskeletal abnormalities. AI contributes to better preoperative planning and helps while performing operations by augmented reality and robotic systems, so operation becomes safer and more accurate. In postoperative care, AI is able to track a patient's progress, modify treatment regimens and oversee chronic illnesses, thus enabling individualized patient attention. This paper aims to review existing usage, future prospects, and the implications of AI in treating children with orthopedic disorders in order to highlight the effectiveness of the tool in enhancing the health of children and the development of pediatric orthopedics as a specialty.

Background: Respiratory therapy is an emerging profession that has existed in India since 1995. Respiratory therapy students will play a significant role in strengthening various aspects of healthcare in the future. There are no validated instruments to evaluate students’ perceptions of their careers and satisfaction with the learning resources. The primary objective of the current study is to develop and validate a structured questionnaire (SQ) for respiratory therapy students in India, encompassing all the components of their career development and satisfaction. Methods: Based on the literature review and content validity from respiratory therapy experts through multiple focused group discussions, a reliable SQ was generated with 40 items based on the Likert scale. After getting institutional ethics clearance and informed consent, the SQ was administered to 904 respiratory therapy students across the country. We performed principal component analysis (PCA), structural equation modeling, and confirmatory factor analysis (CFA) for the global fit. Cronbach’s alpha was performed to estimate the internal consistency. Results: The PCA generated a 4-factor model, and internal consistency for the total scale exceeded the standard criterion of >0.70. Satisfactory goodness of fit data were yielded from CFA. Average variances extracted were higher than the correlation coefficients of the factors, which show sufficient discriminant validity. Conclusion: This study shows a clinically acceptable model, it fits and suggests the possibility of applying a SQ to a respiratory therapy student with relatively good construct validity and internal consistency, based on the results of CFA.

The dynamic scheduling problem (DSP) in unreliable flexible manufacturing systems (UFMSs) with concurrency, conflicts, resource sharing, and sequential operations is a complex optimization problem that requires the use of efficient solution methodologies. The effectiveness of scheduling UFMSs relies on the quality of equipment maintenance. Currently, UFMSs with consistently large queues of parts awaiting service employ a repair-after-failure approach as a standard maintenance procedure. This method may require unexpected resources, incur costs, consume time, and potentially disrupt the operations of other UFMSs, either partially or fully. This study suggests using a predictive maintenance (PdM) strategy that utilizes the Internet of Things (IoT) to predict and avoid early mechanical equipment failures before they happen in UFMSs, thereby reducing unplanned downtime and enhancing reliability. Therefore, the objective of this paper is to construct timed Petri net (TPN) models using the IoT for the PdM configuration of mechanical equipment in the dynamic scheduling problem of UFMSs. This necessitates that users represent the specific problem using TPNs. The process of PN modeling requires the utilization of domain knowledge pertaining to the target problems as well as to machine information. However, it is important to note that the modeling rules for PNs are straightforward and limited in number. Consequently, the TPN model is applied to generate and formulate mixed-integer linear programming (MILP) instances accurately. This is done to identify the optimal production cycle time, which may be implemented in real-life scenarios. Several UFMS instances are used to demonstrate the applications and effectiveness of the proposed method. The computational results demonstrate that the proposed method shows superior solution quality, effectively solves instances for a total of 10 parts and 6 machines, and achieves a solution in a reasonable CPU time.

Electron beam melting (EBM) as one of the relatively new metal AM techniques showed promising and increasing applications. Therefore, there is a need to evaluate the quality of the EBM process using its critical quality characteristics. However, EBM and different AM process parts have many functionally or statistically correlated quality characteristics. Consequently, the quality characteristics of the EBM process should be evaluated together. Therefore, this research aims to evaluate the quality of the EBM process using a multivariate process capability index (MPCI). In this study, the dimensional accuracy in different directions is considered as a quality characteristics. The proposed methodology involves producing a large sample of small specimens of square shape using EBM technology. Three critical dimensions of the specimen in the X, Y, and Z axis are investigated as quality characteristics. The dimensions of quality characteristics are measured using a precise measurement device. The normality and stability assumptions of the collected data are investigated using skewness measure, and multivariate process control chart respectively. Then a large sample of the multivariate normal data is simulated using computer software to estimate the percent of nonconforming (PNC) from the established specification limits, which is used to estimate MPCI. Finally, the capable tolerance of the process is estimated and the sensitivity analysis of variation is investigated. The results show the capability of the EBM process under different specification limits designations. Estimating MPCI revealed that the EBM process is capable under very coarse limits only. Moreover, the sensitivity analysis showed that variation in quality characteristics data is very sensitive for MPCI estimation, especially variation in width quality characteristic.

The global coronavirus disease (COVID-19) epidemic can be partially managed by vaccines; however, the public must be informed about the safety of COVID-19 vaccines to avoid hesitancy. Therefore, it is important to know the safety profile of the COVID-19 vaccine by comparison to that of a well-known vaccine, such as the influenza vaccine. Hence, this retrospective descriptive study was conducted to evaluate and compare the number of adverse effects (AEs) reported to the Vaccine Adverse Event Reporting System (VAERS) for both COVID-19 and influenza vaccines, identify the most common AEs of each vaccine, and compare the frequency and outcomes of using COVID-19 and influenza vaccines in the U.S. population. Surveillance reports from 1st December 2020 to 8th October 2021 of both vaccines were retrieved from the U.S. VAERS. A total of 544,025 and 15,871 reports of post-COVID-19 and - influenza vaccine AEs were reported to the VAERS, respectively. Females reported > 58% and nearly 70% of influenza - and COVID-19 vaccine-associated AEs, respectively. The estimated incidence rates of AEs associated with COVID-19 and influenza vaccines in the U.S. were 1.36 and 0.12 per 1,000 persons, respectively. The incidence of AEs was higher among COVID-19 vaccine recipients than that among influenza vaccine recipients. COVID-19 vaccine recipients have a two-fold higher risk of mortality and life-threatening events than influenza vaccine recipients. However, most of the reported AEs were similar between the two vaccines in terms of symptoms.

Abdullah K Al-Ahmari Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Riyadh, Saudi ArabiaCorrespondence: Abdullah K Al-Ahmari, Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia, Tel +966 11 588 6082, Fax +966 11 588 6000, Email a.alahmari@psau.edu.saPurpose: Data regarding hypertension prevalence among patients with rheumatoid arthritis in Saudi Arabia are scarce. This study was aimed at estimating the prevalence of hypertension and its associated risk factors among patients with rheumatoid arthritis in Saudi Arabia.Patients and Methods: This was a cross-sectional study of adult patients with rheumatoid arthritis who presented at the OPD of two major hospitals in Riyadh city. Patient information such as demographic characteristics, comorbidities, drug use, and other clinical data were captured through medical record review and supplemented by patient interviews. Multivariate logistic regression was used to identify the significant factors for hypertension.Results: The prevalence of hypertension was found in 32.35% of the 1490 rheumatoid arthritis patients who participated in our study. Logistic regression analyses revealed that advanced age, female sex, low education level, unemployment, smoking, and consulting with physicians less than two times within the past 12 months were risk factors for increased hypertension prevalence among patients with rheumatoid arthritis. A significantly higher risk of hypertension was observed among RA patients with obesity, diabetes, hyperlipidemia, cancer, kidney disease, osteoporosis, and Parkinson’s disease than among patients without these comorbidities.Conclusion: Hypertension is highly prevalent among patients with rheumatoid arthritis, and advanced age, sex, low educational level, unemployment, smoking, and comorbidities are risk factors for increased hypertension prevalence.Keywords: blood pressure, prevalence, rheumatoid arthritis, risk factors, Saudi Arabia

The rapid advancement of additive manufacturing (AM) requires researchers to keep up with these advancements by continually improving the AM processes. Improving manufacturing processes involves evaluating the process outputs and their conformity to the required specifications. Process capability indices, calculated using critical quality characteristics (QCs), have long been used in the evaluation process due to their proven effectiveness. AM processes typically involve multi-correlated critical QCs, indicating the need to develop a multivariate process capability index (MPCI) rather than a univariate capability index, which may lead to misleading results. In this regard, this study proposes a general methodological framework for evaluating AM processes using MPCI. The proposed framework starts by identifying the AM process and product design. Fused Deposition Modeling (FDM) is chosen for this investigation. Then, the specification limits associated with critical QCs are established. To ensure that the MPCI assumptions are met, the critical QCs data are examined for normality, stability, and correlation. Additionally, the MPCI is estimated by simulating a large sample using the properties of the collected QCs data and determining the percent of nonconforming (PNC). Furthermore, the FDM process and its capable tolerance limits are then assessed using the proposed MPCI. Finally, the study presents a sensitivity analysis of the FDM process and suggestions for improvement based on the analysis of assignable causes of variation. The results revealed that the considered process mean is shifted for all QCs, and the most variation is associated with part diameter data. Moreover, the process data are not normally distributed, and the proposed transformation algorithm performs well in reducing data skewness. Also, the performance of the FDM process according to different designations of specification limits was estimated. The results showed that the FDM process is incapable of different designs except with very coarse specifications. [ABSTRACT FROM AUTHOR]

The study aimed to determine the educational, academic, and cultural requirements to teacher preparation in order to enhance the transition to high school tracks from the point of view of the faculty members at the College of Education. The study also aimed to reveal the statistically significant differences between the responses of the study sample that are attributed to the variables: gender, degree, and experience. The study used the descriptive survey method, and the questionnaire as a tool for data collection. The study sample consisted of 208 faculty members at the College of Education. The results showed that the educational requirements for teacher preparation to enhance the transition to high school tracks was very high, as the arithmetic average of the total score was 4.50. Likewise, the consensus in favor of both academic and cultural requirements was very high, as the arithmetic average of the total score was 4.48 and 4.25, respectively. Finally, the results revealed no statistically significant differences attributed to variables of gender, academic degree, and experience. [ABSTRACT FROM AUTHOR]

The evaluation of manufacturing processes aims to ensure that the processes meet the desired requirements. Therefore, process capability indexes are used to measure the capability of a process to meet customer requirements and/or engineering specifications. However, most of the manufacturing products have more than one quality characteristic (QC), in which case, the multivariate QCs should be evaluated together using a single capability index. The research in this article proposes a methodology for estimating the multivariate process capability index (PCI). First, the dimensions of the multivariate QCs are reduced into a new single variable using the proportion of the process specification region, by comparing each variable datapoint to its specification limits. Moreover, nonnormal data are transformed to normality using a root transformation algorithm. Then, a large data sample is generated using the parameters of the new variable. The generated data are compared to the specification limits to estimate the percent of nonconforming (PNC). Finally, the capability index of a given process datapoints is estimated using the PNC. Accordingly, managerial insights for the implementation of the proposed methodology in real industry are presented. The methodology was assessed by well-known multivariate samples from four different distributions, in which an algorithm was developed for generating these samples with their given correlations. The results show the effectiveness of the proposed methodology for estimating multivariate PCIs. Also, the results from this research outperform the previous published results in most cases.

Background: A structured respiratory care (RC) program has a greater impact on student's critical thinking and problem-solving. Across India, the RC curricula differ in structure and duration. With the exception of a few well-established central universities and autonomous institutions, many required appropriate educational resources and qualified faculty. The objective of the current study is to determine RT students' perception toward their careers and level of satisfaction with the available learning resources. Materials and Methods: In this cross-sectional survey, 904 respiratory therapy students participated from medical universities and educational institutions across India. Institutional Ethics clearance was obtained from the host institution and students were given basic information regarding the survey. A validated, structured questionnaire was used which consists of 26 questions that cover four domains: Perception (4 items), satisfaction (13 items), curriculum (5 items), and suggestion (4 items). The questions were answered as per the five-point Likert scale. Data analysis was descriptive, and logistic regression was performed to evaluate factors associated with students' satisfaction with the learning resources. Results: The majority of the respondents were female (59%) and belonged (48%) to the age group of

Manal Al Harthi,1,2 Abdulellah Al Thobaity,1 Mohammed Almalki,1 Waleed Al Ahmari1 1Nursing Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia; 2King Faisal Medical Complex, Ministry of Health, Taif, Saudi ArabiaCorrespondence: Abdulellah Al ThobaityNursing Department, College of Applied Medical Sciences, Taif University, P. O. Box 11099, Taif, 21944, Saudi ArabiaTel +966 12-727-2020Email a.thobaity@tu.edu.saIntroduction: Nurses in Saudi Arabia face several challenges in all phases of disaster nursing, such as the infancy of the specialty and a lack of education, preparedness, research, and expertise in both the clinical field and in academics. Overcoming these challenges will help both nurses and the development of the specialty itself in aspects such as policies and procedures, education, and research. Thus, the aim of this study was to explore strategies for improving disaster nursing in Saudi Arabia.Methods: A cross-sectional study with a principal component analysis (PCA) was conducted to identify the factors affecting disaster nursing in Saudi Arabia. The sample of the study was Saudi Arabian nurses, as they are first-line responders in disasters and pandemics.Results: From 800 distributed questionnaires, 569 completed questionnaires were returned, for a response rate of 71%. The findings of the PCA revealed two components that can be extracted from the data. The first is preparedness, which involves 13 items related to the actions that must be taken before a disaster occurs, with a loading range of 0.82 to 0.70. The second factor is the action taken after a disaster occurs, and there are seven items with a loading range of 0.83 to 0.73.Conclusion: For improved disaster nursing, it is essential to develop evaluation tools, create specific nursing legislation for disaster situations, provide personal protective equipment to nurses to minimize the risk of infection, and encourage nurses by appreciating their efforts to minimize their stress level during a disaster. It is also important to make sufficient supplies and equipment available to nurses during a disaster and provide them with psychological support while acknowledging the importance of contact with their families and friends.Keywords: disaster nursing, disaster preparedness, emergency nursing, Saudi Arabia