Communication Errors Research Articles

Prevalence of Language Barriers, Impacts, and Coping Strategies among Medical Students during their Clinical Rotation in Peshawar

Background: This study examines the Prevalence of Language Barriers, Impacts, and Coping Strategies among Medical Students during their Clinical Rotation in Peshawar, an area with a wide range of language diversity. Methods: A cross-sectional survey was conducted among 663 medical students from six medical colleges in Peshawar to assess the prevalence, frequency, and severity of language barriers, their impact on patient interactions, and the coping mechanisms employed by students. Results: The findings indicated that 39.1% of the students faced language barriers during clinical rotations; most of them were female and non-Pashto speakers. A vast proportion (69.1%) felt that these barriers negatively affected patient care due to difficulties in obtaining proper patient history and increased miscommunication. Moreover, students with language barriers reported anxiety and frustration during patient interaction. The primary coping strategy used by students was seeking support from colleagues at 80.7%. Figures showed that only 11.9% of students received formal training to overcome language barriers. Of course, students who received language barrier training were significantly more confident in clinical interactions. Conclusion: These results suggest extreme reforms in medical curricula, such as including many languages and cultural training programs to overcome language barriers; this would better prepare the students to work in a multilingual setting, dramatically reducing communication errors, improving patient care, and enriching the education experience in diverse areas.

Navigating High-Stakes Collaboration: A Critical Analysis of Team Dynamics Among Medical Staff in Pressure-Driven Surgical Operations

In high-stakes surgical operations, effective teamwork among medical staff is critical for ensuring patient safety and positive outcomes. This article presents a critical analysis of team dynamics under pressure, focusing on communication, role clarity, leadership, stress management, and team cohesion. Using case studies and an extensive review of existing literature, the analysis examines the challenges faced by surgical teams, including breakdowns in communication, hierarchical barriers, and stress-induced errors. Additionally, the article explores successful interventions that promote collaborative skills and resilience, such as closed-loop communication protocols, role-flexibility training, and leadership development. The findings suggest that structured teamwork training and stress-management strategies significantly enhance collaborative performance in pressure-driven surgical scenarios. This analysis underscores the importance of continuous team development and adaptive leadership in mitigating risks and improving patient outcomes.

ENGLISH PRONUNCIATION PROBLEMS AMONG VIETNAMESE LEARNERS OF ENGLISH: AN EMPIRICAL STUDY

In oral communication, inaccurate pronunciation or pronunciation errors may create serious consequences, such as conversational discomfort, business disruption, and negotiation failure, leading to miscommunication or, at times, regrettable occupational accidents. Unfortunately, in a number of educational institutions in Vietnam, inadequate attention has been paid to the teaching and learning of English pronunciation. This is why Vietnamese learners of English seem to have neither full awareness, and thus, nor good performance of English pronunciation. Through qualitative and quantitative data collected from an experimental survey, the study indicates that non-English majors at University of Transport, Ho Chi Minh City (UTH) encounter various pronunciation problems due to various reasons, both objective and subjective. The study also results in strategies and techniques that may be beneficial to both the lecturers and the students in teaching and learning English pronunciation at UTH in particular and in the Vietnamese contexts in general.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0802/a.php" alt="Hit counter" /></p>

A case study of offshore evaporation ducts in northeastern Taiwan during summer time

Over the ocean northeast of Taiwan, the summer is hot and the air-sea interaction is strong, so it is easy to produce various kinds of atmospheric duct phenomena due to the rapid change of temperature and water vapor in the vertical direction. Among the various atmospheric duct phenomena, Evaporation Duct (ED) occurs frequently and for a long time, which often affects electromagnetic wave transmission, causing errors in communication and search radar signals, and is the most valuable for research. In this study, we used an unmanned aerial vehicle (UAV) with a Storm Tracker (ST) which is a mini meteorological observation device to measure air temperature, pressure, and relative humidity near the ocean to get the Evaporation Duct Height (EDH) of Yilan in northeastern Taiwan in the summer of 2022. Through the 5-m vertical resolution observation, we understand the atmospheric factors affecting the EDH. Throughout the summer observation period, various types of atmospheric ducts also manifest in the northeastern region of Taiwan. In the numerical simulation, we use the WRF model with two sets of different boundary layer parameterizations, Mellor-Yamada-Janjic (MYJ) and Yon-Sei University (YSU), and import the simulation results into the Paulus-Jeske (P-J) ED model to compute the EDH. It was found that the EDH calculated by WRF using the MYJ boundary layer parameterization imported into the P-J ED model was closer to the observed results. This method can forecast the EDH in the northeastern Taiwan sea area, which is valuable for application.

A 5-Year retrospective analysis of adverse events in dentistry at the Dental Hospital, Faculty of Dentistry, Chulalongkorn University

BackgroundPatient safety is a critical concern in dentistry. Adverse events (AEs) can harm patients, increase costs, and decrease satisfaction. Understanding AE types and frequencies is crucial for effective risk management and quality improvement. This study analyzes incident reports to identify preliminary incident patterns as a starting point for developing risk management strategies. However, under-reporting limits the ability to identify true incident patterns, highlighting the need for improved reporting systems and encouragement of incident reporting. Further research is underway to develop such a system and promote reporting to ensure sufficient data quality for effective risk management.MethodsA retrospective analysis of 1,618 incident reports from December 2018 to August 2023 was conducted. A validated classification system, developed from a 5-year retrospective analysis and approved by 14 experts, categorized patient safety incidents, aligning with Thailand’s Hospital Accreditation standards. Descriptive statistics summarized AE frequency and distribution.ResultsOf the reports, 752 were patient safety, 503 personnel safety, and 363 organizational safety incidents. Top patient safety incidents included medical record errors (176), accidental damage (66), post-operative complications (65), medical emergencies (64), and communication errors (53). Personnel safety incidents involved inappropriate working conditions (135) and work-related injuries with contact transmission risk (117). Organizational safety incidents mainly concerned policy and operational processes (131).ConclusionsThis study reveals the preliminary patterns of adverse events (AEs) in dental settings and underscores the limitations due to under-reporting, which affect the ability to fully understand true incident patterns. To effectively manage risks, there is a critical need for improving the existing incident reporting system and encouraging a culture of comprehensive reporting among dental professionals. Future efforts should focus on enhancing reporting systems to ensure high-quality data, enabling better identification of incident trends and supporting targeted risk management strategies to improve patient safety in dentistry.

Ultra‐Low BER Encrypted Communication Based on Self‐Powered Bipolar Photoresponse Ultraviolet Photodetector

AbstractUnderwater visible light communication often faces risks such as susceptibility to external light source interference, signal distortion, and information leakage. The cuprous oxide modified gallium oxide nanorod arrays detector prepared in this study can generate bipolar photocurrents under dual‐wavelength ultraviolet light without external bias voltage. Based on it, the constructed self‐powered ultraviolet ASCII code communication system not only reduce power consumption but also significantly enhance anti‐interference capability. Furthermore, the developed solar‐blind ultraviolet AMI and HDB3 ternary code communication systems can realize non‐visible light secure communication and automatic error correction. Notably, the encrypted communication system assembled using the additive property of bipolar photocurrents can also significantly improve communication security and reliability, whose bit error rate is only 0.26‰. This achievement contributes to technical advancements in underwater channel encryption and provides valuable insights for the further application of encrypted communication coding techniques.

Biologically Oriented Preparation Technique Through a Digital Workflow, a Case Report.

In every prosthetic treatment, the final purpose of the restoration is to restore function and esthetics for the patient, respecting biology and anatomical parameters. Regarding full coverage restorations, there are some factors to take into consideration: like the finish line (chamfer, shoulder, featheredge, etc.), the management of the provisional restoration and tissue healing, the material for the final restoration, and the impression technique. All these aspects will determine the treatment process and its possible results. In recent years, vertical preparation and more specifically biologically oriented preparation technique has generated great interest since its introduction in prosthodontics, changing the periodontal tissues, and providing long-term stability. With this technique, the objective is to change the position of the gingival margin, moving it more apically or coronally, depending on the modifications of the provisional. The relining of the provisional is a fundamental step of this technique: the intrasulcular part of the provisional is modified giving a new emergence profile and providing an augmentation of the tissue in the healing process. In vertical preparation, there is no predetermined margin. The dental technician should position the finish line more apically or coronally, depending on the depth of the sulcus and on the esthetic needs. Ceramic restorations should not invade the epithelial attachment, otherwise it may cause biological and mechanical problems, repetition of the impression, and of the crown restoration, which lead to increased clinical and laboratory time usage as well as expenses. One challenge is communicating the shape and contour of the temporary restoration to the dental lab to ensure accurate information for the final restoration. Finally, the objective of this article is to describe a technique for transferring all necessary information of the provisional and obtaining a predictable result for the final restoration by using an intraoral scanner system and the fabrication of two 3D printed prototypes. One for the final volume of the crowns and the other for the finish line position. The fabrication of 3D printed prototypes allows for a more predictable final restoration, reducing possible communication errors between clinician and technician when restoring with biologically oriented preparation technique. In any esthetic treatment where the restoration does not have a predetermined margin, it is possible with this additional clinical step to provide a more esthetic outcome.

Optimisation of synchronisation control parameters for enhanced bilateral teleoperation system

Abstract Bilateral teleoperation systems encounter challenges in achieving synchronisation between master and slave robots due to communication time delays. This paper addresses the instability caused by these delays and proposes a solution through advanced control algorithms. Nonlinear optimisation algorithms might only sometimes deliver solutions in the allotted time, particularly when handling complicated, high-dimensional issues or when optimisation iterations are extensive. The study first develops a comprehensive mathematical model encompassing the dynamics and communication intricacies of both master and slave sides in teleoperation. By recognising the limitations of existing proportional-derivative controllers in compensating for communication errors, a sequential quadratic programming-proportional-integral-derivative (SQP-PID) controller is introduced. This controller accumulates and rectifies synchronisation delay errors, ensuring precise control without steady-state deviations. The proposed SQP-PID controller stands out for its ability to handle steady-state errors effectively, offering swift response and maintaining stability. Leveraging the SQP optimisation algorithm, it intelligently tunes the parameters, minimising synchronisation errors. The approach capitalises on the simplicity, performance, and robustness of the SQP-PID controller, providing a promising avenue for enhancing bilateral teleoperation systems’ accuracy and stability, maintaining initial discrepancy with a best fitness value of 0.98 % in varied operating conditions.

Performance Evaluation of the Two-Input Buck Converter as a Visible Light Communication High-Brightness LED Driver Based on Split Power.

This work proposes a high-efficiency High-Brightness LED (HB-LED) driver for Visible Light Communication (VLC) based on a Two-Input Buck (TIBuck) DC/DC converter. This solution not only outperforms previous approaches based on Buck DC/DC converters, but also simplifies previous proposals for VLC drivers that use the split power technique with two DC/DC converters: one is in charge of the communication tasks and the other controls the biasing of the HB-LED (i.e., lighting tasks). The real implementation of this scheme requires either two input voltage sources, one of which is isolated, or one DC/DC converter with galvanic isolation. The proposed implementation of splitting the power is based on a TIBuck DC/DC converter that avoids the isolation requirement, overcoming the major drawback of this technique, keeping high-efficiency and high communication capability thanks to the lower voltage stress both across the switches and at the switching node. This fact allows for the operation at very high frequency for communication purposes, minimizing switching power losses, achieving high efficiency and providing lower filtering effort. Moreover, the duty ratio range can also be adapted to the useful voltage range of the HB-LED load to maximize the resolution on the tracking of the output volage. The power is split by means of an auxiliary Buck DC/DC converter operating at low switching frequency, which generates the secondary voltage source needed by the TIBuck DC/DC converter. This defines a natural split of power by only processing the power delivered for communications purposes at high frequency. A 7 W output-power experimental prototype of the proposed VLC driver was built and tested. Based on the experimental results, the prototype achieved 94% efficiency, reproducing a 64-QAM digital modulation scheme and achieving a bit rate of 1.5 Mbps with error in communication of 12%.

IoT Based Advanced Cardiac Arrest Detection System

Internet of Things (IoT) based Advanced cardiac Arrest Detection system have an expansive potential of becoming an integral part of the future medical system. In particular, these systems can play life-saving roles for monitoring of patients with critical health issues. Any health care monitoring system must be free from incorrect data, which may arise because of instrument failure or communication errors. In this project, to detect reliability and accuracy of data obtained by the IoT-based remote health monitoring. This project makes a use of MAX30100 (heartbeat & oxygen), ESP8266 Wi-Fi module and Arduino nano. The main controlling device of the project is Arduino nano microcontroller. Arduino will continuously read the heartbeat and spo2 value through MAX30100 sensor and will be sent to the blynk mobile application through esp8266 Wi-Fi module. User can access this device using smart mobile from anywhere in the world. To achieve this task microcontroller loaded program written in embedded C language.

The Post-Operative Handoff: Perceptions and Preferences of Pediatric Hospitalists and Surgeons.

Postoperative communication errors contribute to patient harm and excess costs. There are no existing standards for postoperative handoff to the acute care inpatient unit. We aimed to compare the experiences and preferences of pediatric hospitalists and surgeons about the content and timing of this handoff. We conducted a cross-sectional multisite survey of pediatric hospitalists and surgeons at 4 hospitals using a novel survey tool developed through a systematic 7-step process. We collected data on the perceived frequency of communication for 37 handoff elements and how essential each element was for an ideal handoff. We used 5-point Likert scales of communication frequency and essentialness. Respondents identified perceived and preferred handoff timing. Mention frequency and timing data were analyzed with the Mann-Whitney U test and Fisher's exact test, respectively. Seventy hospitalists (61%) and 27 surgeons (25%) responded to the survey. Over half of both hospitalist and surgeon respondents rated 13 handoff elements a 5 on the essentialness Likert scale. Surgeons perceived that 33 handoff elements were mentioned significantly more frequently than perceived by hospitalists (P < .05). Of hospitalists, 58% preferred that handoff occur immediately before the patient leaves the postanesthesia care unit. Of surgeons, 60% preferred that handoff occur immediately postoperatively. The 13 core elements we identified may facilitate the development of a standardized handoff checklist for postoperative communication between surgeons and hospitalists on acute care units. Areas of future study could include checklist validation, audits of handoff practice, and qualitative research on handoff preferences.

WP8.2 - Human Factors Analysis of CORESS cases using the NOTSS Framework

Abstract Aims Determine human factors implicated in cases submitted to the Confidential Reporting System in Surgery (CORESS), using the non-technical skills for surgeons (NOTSS) framework. Methods Consecutive cases submitted to CORESS, between 2005 and 2011 were evaluated as an interim analysis. The type of case, whether patient harm occurred, Clavien-Dindo (CD) classification, and the location of the incident were collected. Demographic data was not collected because they are often changed to protect patient identification. Each case was reviewed according to the non-technical skills for surgeons (NOTSS) taxonomy. Results There were 100 cases included in this interim analysis. The most common types of cases were delayed diagnosis (n=19), known complications (n=10), near misses (n=10), poor surgical technique (n=9), misuse of equipment/device (n=8), and wrong site surgery (n=5). Two-thirds of patients were harmed, with complications ranging from minor to life-threatening (9 CD I, 10 CD II, 32 CD III, 12 CD IV), and 4 resulting in death (CD V). Incidents occurred most frequently in the operating theatre (n=54), the ward (n=16), or the emergency department (n=9). There were 71 incidents that endangered patient safety related to deficiencies in situational awareness, 59 to poor communication and teamwork, 48 to poor decision-making, and 48 related to leadership failures. Conclusions The main human factors implicated in surgical patient safety incidents related to errors in situational awareness, communication and teamwork, and to a lesser extent, decision-making, and leadership. Efforts to prevent medical errors should be focused on clinician human factors training.

Public perceptions of reportable safety events and risks in United States primary care

Introduction: Patients may not feel responsible for reporting safety events, and social norms may prevent patients from questioning health care providers’ judgment. There is a paucity of research regarding public awareness of reportable safety events/risks. Educating the public about reporting is paramount in error prevention. Because more than 70% of errors (e.g., errors in diagnosis, communication errors, unsafe medication practices, and care fragmentation) occur in primary care settings, the purpose of this study was to explore public perceptions of when to report safety events/risks in these settings. Method: System-level primary and outpatient facility safety incident scenarios conducive to safety events/risk reporting were developed and administered via online survey methodology. Following completion of the scenario questions, participants were asked a single open-text item: “As you were reading the scenarios above, what did you think makes an event/risk ‘reportable’?” Results: At least one-third of participants responded incorrectly in 70% of the scenarios. The percentage of incorrect responses ranged from 5.2% to 62.3% with “unwitnessed falls” and “nursing scope of practice” queries incorrectly reported at 44.5% and 53.9%, respectively. Rationales for inappropriate events/risk reporting included “risk prediction at the management/system level,” “legal repercussions/protection (e.g., negligence, legal responsibility to patient),” “violations of scope of practice/professional expectations,” “degree of potential/actual lethality,” and “personnel errors.” Conclusion: This study revealed a gap between understanding why to report an event/risk and when to correctly report (or not report) an actual healthcare issue. Practical applications: Awareness of reasons for correctly reporting incidents and how correct reporting builds a culture of safety needs to be strengthened.

Peer review for handoff education in a transition to residency course: A prospective cohort study.

Association of American Medical Colleges (AAMC) and Accreditation Council for Graduate Medical Education (ACGME) mandate training in handoff delivery for students and residents. Communication errors, including errors during handoffs of patient care, account for over 2/3 of sentinel events. This study aims to assess the effectiveness of peer-assisted learning (PAL) in handoff education within a longitudinal framework. This study involved the analysis of fourth-year medical students (n = 67) enrolled in a transition to residency program designed to reinforce skills essential for success in internal medicine residencies. We modified the I-PASS handoff rubric for a single-encounter evaluation. Before attending the transitions of care workshop, students submitted one written handoff report. During high-fidelity simulation sessions, peers evaluated the written document as well as verbal handoffs, while faculty evaluated a recorded verbal version. The primary outcome measured was improvement in handoff quality and accuracy over time and secondary outcomes compared peer- and self-evaluations to faculty assessments. Overall, students demonstrated a statistically significant improvement in handoff quality and accuracy across all scoring criteria after completing the peer evaluation process. Peer evaluations did not demonstrate statistically significant differences in scores for quality or accuracy questions as compared to faculty. Peer evaluators effectively assessed handoff reports using the modified I-PASS checklist yielding outcomes similar to faculty while providing feedback. These findings provide exciting evidence that should prompt training programs to consider incorporating standardized peer review into handoff education for medical students and, potentially, residents. The detailed evaluation of individual handoff events fosters feedback skills essential for ongoing professional growth and clinical excellence.

Exploring the Therapeutic Potential of Phytoconstituents for Addressing Neurodegenerative Disorders.

Neurodegenerative disorder is a serious condition that is caused by abnormal or no neurological function. Neurodegenerative disease is a major growing cause of mortality and morbidity worldwide, especially in the elderly. After World War Ⅱ, eugenics term was exterminated from medicines. Neurodegenerative disease is a genetically inherited disease. Lifestyle changes, environmental factors, and genetic modification, together or alone, are involved in the occurrence of this disorder. The major examples of neurodegenerative disorders are Alzheimer's and Parkinson's disease, in which apoptosis and necrosis are the two major death pathways for neurons. It has been determined from various studies that the etiology of the neurodegenerative disease involves the role of oxidative stress and anti-oxidant defence system, which are prime factors associated with the activation of signal transduction pathway that is responsible for the formation of synuclein in the brain and manifestation of toxic reactions in the form of functional abnormality, which ultimately leads to the dysfunction of neuronal pathway or cell. There has not been much success in the discovery of effective therapy to treat neurodegenerative diseases because the main cause of abnormal functioning or death of neurons is not well known. However, the use of natural products that are derived from plants has effective therapeutic potential against neurodegenerative disease. The natural compounds with medicinal properties to prevent neurological dysfunction are curcumin, wolfberry, ginseng, and Withania somnifera. The selection and use of natural compounds are based on their strong anti-inflammatory and anti-oxidant properties against neurodegenerative disease. Herbal products have active constituents that play an important role in the prevention of communication errors between neurons and neurotransmitters and their respective receptors in the brain, which influence their function. Considering this, natural products have great potential against neurodegenerative diseases. This article reviews the natural compounds used to treat neurodegenerative diseases and their mechanisms of action.

Perbandingan Motivasi Kerja Ruang Rawat Inap dan Ruang Operasi dalam Pelaksanaan Pendokumentasian di RS MTSJ

Based on the results of a preliminary study conducted by researchers in January in the inpatient room and operating room at MTSJ Hospital, it was found that there was still a lot of incomplete documentation. Of the 10 murder documentation, 7 of them are still incomplete, incomplete documentation, starting from not including all the acts committed by the murder, inaccuracy in the signature of informed consent between the witness and the patient, unavailability in the form of a fall risk for pediatric and geriatric patients. Documentation at MTSJ Hospital still receives little attention, so care documents are still found whose contents are incomplete. Some problems with documenting nursing care include: lack of motivation in documenting nursing care, writing documentation is considered time-consuming and focuses on patient care. Incomplete documentation will cause losses to clients because important information related to their care and health conditions is neglected. Inefficient and ineffective documentation due to inadequate quality and accuracy causes communication errors between nurses and other professions. Based on the description above and the results of preliminary research, researchers are interested in researching the comparison of work motivation in inpatient rooms and operating rooms with the implementation of documentation at MTSJ Hospital.

Human error identification and risk assessment in loading and unloading of petroleum products by road trucks using the SHERPA and fuzzy inference system method

Human error constitutes one of the primary causes of accidents, particularly in the context of loading and unloading operations involving road trucks, especially those carrying petroleum products. The process of identifying and evaluating human errors within these operations involves several key steps. Initially, all sub-tasks associated with loading and unloading are meticulously identified and analyzed utilizing Hierarchical Task Analysis (HTA), achieved through direct observation, document examination, and interviews. Subsequently, potential human error modes within each task are delineated using the Systematic Human Error Reduction and Prediction Approach (SHERPA). Finally, essential data for determining the criticality, probability, and severity of each error are gathered through expert elicitation and the application of Fuzzy Inference Systems (FIS).Through the analysis of SHERPA worksheets, a total of 37 errors during loading operations and 14 errors during unloading operations of petroleum products were identified. Among these errors, the predominant category during loading operations was action errors, comprising 31 instances, while communication errors were the least frequent, occurring only twice. Similarly, action errors were most prevalent during unloading operations, constituting 13 instances. These errors were further categorized and ranked based on their risk levels, resulting in 27 levels for loading operations and 12 levels for unloading operations.The consistent occurrence of action errors underscores the need for implementing control measures to mitigate their frequency and severity. Such strategies may include periodic training sessions to reinforce proper work procedures and the development of monitoring checklists, among other interventions.

Federated Learning with Homomorphic Encryption for Ensuring Privacy in Medical Data

Federated Learning (FL) is a machine learning methodology that allows remote devices to collectively train a learning system without sharing their data. FL-based methods provide enhanced secure privacy by transmitting only localized model variables, learned with local information, from dispersed devices to a centralized controller. There is a potential for a centralized server or malicious individuals to deduce or get sensitive private data by analyzing the structure and variables of regional learning networks. This study incorporates the FL process into the deep learning process of medical prototypes in an Internet of Things (IoT)-based medical facility. A Secured Medical Homomorphic Encryption Algorithm (SMHEA) is proposed in this research to ensure medical data privacy. Cryptographic primitives, such as masking and homomorphic cryptography, are used to enhance the security of local modeling. This prevents adversaries from deducing confidential health information via assaults like model restoration or modeling inversion. The primary determinant for assessing the regional modeling's contributions to the universal model during each training stage is the quality of the databases possessed by various individuals rather than the typically used metric of database dimension in deep learning. A dropout-tolerant approach is suggested, where the FL procedure would continue as long as the total amount of online customers remains over a certain level. By doing a security evaluation, it is evident that the suggested approach effectively ensures data privacy. Theoretical analysis is conducted on accuracy, computation time, and communication error. An example of clinical applications is the categorization of skin lesions using training photos from the HAM10000 medical database. The experimental findings demonstrate that the suggested system had favorable performance and privacy preservation outcomes compared to current methods.

FACTORS RELATED TO THE QUALITY OF HANDOVER OF SITUATION, BACKGROUND, ASSESSMENT, RECOMMENDATION (SBAR) METHODS ON INTERNAL PATIENT TRANSFER

Communication errors are one of the causes of patient safety incidents. Handover of internal patient transfers using the SBAR methodis a form of communication whose implementation has not been carried out optimally. Purpose: To determine the factors associatedwith the quality of the SBAR handover method in internal patient transfers. Research method: Type of correlational quantitativeresearch. Cross-sectional research design. The population consisted of 94 nurses who carried out internal patient transfers. Thesample consisted of 76 nurses who transferred level 0 patients. The sampling technique uses purposive sampling. Measuring toolsuse questionnaires and observation sheets. Statistical tests use the Chi-Square test. Results: Nurse attitude (P-value = 0.000) andOdds Ratio 8.543, receive motivation (P-value = 0.003) and Odds Ratio 5.315, Head of Space leadership (P-value = 0.001) and OddsRatio 6.367, and head of room supervision (P-value = 0.002) and Odds Ratio 5.769. has a P-value of &lt;0.005, using Chi-Square Testanalysis and Logistic Regression to see the most influential variable, nurse attitude. Conclusion: The attitude sub-variable is the mostinfluential on the quality of SBAR method handover in internal patient transfer. Suggestion: Hospitals must conduct periodic andcontinuous evaluations of handover activities. The nurse's attitude that needs to be improved is the understanding of the sta ges andadjustment of the appropriate internal transfer time of the patient.

Enhancement of Texas wind turbine power predictions using fractional order neural network by incorporating machine learning models to impute missing data

In real-world datasets, missed data is often expected due to sensor errors, environmental conditions, communication errors, and other technical limitations. These factors can affect the accuracy of power predictions, particularly in wind speed and direction parameters. Enhancing the accuracy of wind energy forecasts and maintaining the electrical grid’s stability are essential in addressing related challenges. This paper proposes a bidirectional long short-term memory (Bi-LSTM) model to forecast missed wind speed and direction data to address these issues. In addition, a novel fractional-order neural network (FONN) with various developed fractional activation functions presents enhanced wind power prediction using forecasted missing wind speed and direction data. The performance of the FONN model is demonstrated in four comprehensive case studies on the Texas wind turbine dataset. The first case study uses wind speed, direction, pressure, and air temperature data. The second case study uses pressure, air temperature, wind speed, and forecasted wind direction data. Similarly, pressure, air temperature, wind direction, and forecasted wind speed data are used in the third case study. The final case study uses pressure, air temperature, and forecasted wind speed and direction to predict power. The proposed models’ performance is evaluated using mean square error and coefficient of determination metrics.