Situational Awareness Research Articles

Pengaruh Situational Awareness dan Work Engagement Terhadap Turnover Intention dengan Organizational Commitment Sebagai Variabel Intervening Karyawan Rumah Sakit Annisa Cikarang

Annisa Hospital Human Resource Development data shows a tendency to increase employee turnover. From the 2022-2023 data, the percentage increase in turnover was 14.95%, rising to 16.64%. This turnover value is said to be quite high and has increased in percentage. This study aims to test the effect of situational awareness, work engagement on turnover intention with organizational commitment as an intervening variable for employees. The approach used is a quantitative approach. The sample used in this study were 169 permanent employees. Sampling was carried out by simple random sampling. Research data were obtained from filling out questionnaires and analyzed using the SEM PLS technique. The results of this study indicate that situational awareness, work engagement, organizational commitment each have a negative effect on turnover intention. Situational awareness and work engagement each have a positive effect on organizational commitment. Organizational commitment acts as an intervening factor for the influence given by situational awareness and work engagement on turnover intention. In order to reduce the high turnover intention, effective communication is needed, providing bonuses to employees according to their target achievements, providing enthusiasm and motivation to employees of Annisa Cikarang Hospital.

Unravelling situational awareness of multi-tasking pedestrians through average gaze fixation durations: An accelerated failure time modelling approach.

Unravelling situational awareness of multi-tasking pedestrians through average gaze fixation durations: An accelerated failure time modelling approach.

CRCPD E-43 Committee for Interagency Environmental Data Sharing and Communications Endorsed RadResponder Threshold Sets.

Situational awareness is critical in radiological emergency response as it enables responders to understand and interpret real-time data to make informed decisions during high-stress situations. Effective situational awareness involves collecting accurate data on radiation levels, contamination zones, and potential exposure risks, and visualizing this data in a comprehensible format. Tools like RadResponder play a key role in this process by allowing users to assign severity levels to data records and view them on an event map, thus facilitating rapid and informed decision-making. The CRCPD E-43 committee has developed enhanced threshold sets for RadResponder to improve situational awareness during radiological incidents. These threshold sets, based on science and informed by nationally recognized reference documents or regulations, are designed to help responders quickly assess radiation levels and make informed decisions regarding public safety and emergency worker doses. By providing clear, easily identifiable values and a standardized approach to data visualization, these threshold sets enhance the effectiveness of radiological emergency response efforts. The committee also recommends upgrades to the RadResponder system for better visibility and management of threshold sets, ensuring responders can efficiently access vital information during emergencies.

Interprofessional Learning and Improving at the Paediatric Ward: A Participatory Action Research Practising Safety-II Theory.

In the complex setting of hospitals, professionals often lack time to improve patient safety. Safety-II theory advocates integrating safety improvement, patient participation, and interprofessional learning and proposes learning frequently from practice variability. The aim of the research was to understand how interprofessional workplace teams can learn and improve daily from practice variability. Participatory action research (PAR) was conducted at a Dutch educational hospital paediatric ward to improve situational awareness in bedside ward-rounds. Methods included 115 semi-structured interviews and participant observations of the interactions. The action research team consisted of a representation of all stakeholders and the first author, who introduced Safety-II concepts to reflect on their practice. The exchange of perspectives between parents, nurses and physicians increased awareness of mutual expectations and experiences prompting individual learning. To foster collective learning at the ward, the research team introduced standards tailored to participants' concerns and stimulated everyday interactions about the ward-round. This approach facilitated daily mutual perspective taking, expectation alignment, and recognition of practice variability, thereby enhancing unit-wide learning and improvement. While aiming at increasing shared situational awareness, multiple improvements emerged simultaneously and unexpectedly including time management, professional pride and job satisfaction. However, participants also discovered that lessons learned did not automatically spread to newcomers. Everyday learning in hospital units can be enhanced through daily interprofessional interactions about expectations and supported by procedural standards. Fostering daily interactions and initiating standards that met participants' concerns required the research team to spend considerable time addressing conflicting priorities. PAR proved to be a valuable and adaptive approach for learning, improving and engaging all stakeholders in a complex setting.

Evaluating sensor tasking strategies for object cataloging in GEO

Evaluating sensor tasking strategies for object cataloging in GEO

Flusion: Integrating multiple data sources for accurate influenza predictions.

Flusion: Integrating multiple data sources for accurate influenza predictions.

TeamSTEPPS® in Home Health.

TeamSTEPPS is a patient safety model that uses a collection of tools and best practices to optimize team performance. It has been widely adopted in the inpatient setting but clinician autonomy has been a barrier in its use. A home healthcare agency began using TeamSTEPPS® and found that it has a positive impact on nurse retention through the use of situational awareness and mutual support tools. Small improvements were made in OASIS outcomes and 30-day hospital readmissions through the use of handoffs and huddles.

Optimal proposal particle filters for detecting anomalies and manoeuvres from two line element data

Optimal proposal particle filters for detecting anomalies and manoeuvres from two line element data

Resilience and Performance of Nontraditional Space Situational Awareness Sensor Architectures

There is increasing interest in the adoption of distributed, multidomain space situational awareness (SSA) sensor architectures as a means of improving both mission performance and resilience while decreasing total cost. One promising concept calls for augmenting legacy terrestrial architectures with opportunistic sensors hosted on government and commercial spacecraft. This research explores this concept by simulating the observability of resident space objects (RSOs) in medium Earth orbit (MEO) and geosynchronous orbit (GEO) by 3300 candidate sensor network architectures. Over a simulated 48 h period, a network composed of 4 terrestrial telescopes and 10 hosted payloads in low Earth orbit revisited each of over 1200 MEO and GEO RSOs in under 8.5 h. This network also proved to be highly resilient, maintaining this revisit rate in an environment in which all terrestrial telescopes were inoperable. In this maximally degraded environment, over 600 space-based sensor networks were still capable of revisiting each RSO in under 24 h. Results of this research suggest that space-based opportunistic hosted payloads stand to concurrently improve the performance and resilience of existing SSA sensor networks used for deep space object catalog maintenance.

Framework of Adaptive Driving: Linking Situation Awareness, Driving Goals, and Driving Intentions Using Eye-Tracking and Vehicle Kinetic Data

Framework of Adaptive Driving: Linking Situation Awareness, Driving Goals, and Driving Intentions Using Eye-Tracking and Vehicle Kinetic Data

Situation Awareness for Cyber resilience: A review

Situation Awareness for Cyber resilience: A review

Space situational awareness systems: Bridging traditional methods and artificial intelligence

Space situational awareness systems: Bridging traditional methods and artificial intelligence

Evaluating the effectiveness of rhythmic visual guidance technology for mitigating driving risks in highway tunnel groups: A simulation study.

Evaluating the effectiveness of rhythmic visual guidance technology for mitigating driving risks in highway tunnel groups: A simulation study.

Comprehensive Evaluation of Remote Tower Controllers’ Situation Awareness Level Based on the Entropy Weight Method (EWM)–TOPSIS–Gray Relational Analysis Model

In recent years, the rapid development of remote tower technology has made it crucial to accurately assess the situational awareness (SA) levels of remote tower controllers. Such an assessment is significant for controller training and remote tower system design. This study employed the SART scale to compare controllers’ SA scores in traditional and remote tower environments. Results revealed significant differences, especially in attention demand and situational understanding. Subsequently, a quantitative analysis of controllers’ perception, understanding, and decision-making abilities was conducted, integrating subjective and objective data. Eye-tracking, heart rate, working memory scales, and communication-coordination scales showed significant results. Experienced controllers had better psychological safety skills, while trainees were more likely to increase vigilance. Moreover, a series of sensitive SA indicators were identified. An evaluation index system was established using the entropy weight method. By calculating the Euclidean distance, Gray relational degree, and comprehensive proximity coefficient, the SA levels of controllers were comprehensively evaluated. The top five important indicators were average blink rate, scan length, average fixation duration, fixation duration, and average pupil diameter. These findings support enhancing air traffic control safety and refining SA assessment for remote tower controllers.

Evaluation of design managers’ views of decision-making: propositions for situational awareness in building design

Building design management (BDM) is a complex, iterative, and highly collaborative process, which poses several challenges for design managers (DMRs). One challenge relates to the diversity of the information required for decision-making and the resulting limited situational awareness (SA). The construction industry has shown interest in the SA concept, although its applications have so far remained confined to construction management and production, rather than design or its management. This geographically limited study, which explores decision-making in building design management from the DMR perspective, specifically explores how situational awareness manifests in DMRs’ decision-making processes. The research data were collected through a literature review, an expert workshop, and expert interviews. The most interesting findings regarding the applicability of the situational awareness concept in BDM relate to the changing roles of the DMR, the changing balance of decision-making power, and the proposal-based decision-making practices in BDM. In this paper, we propose a novel conceptual framework for situational awareness in BDM, thereby contributing to BDM research and encouraging practitioners toward more holistic development of SA systems, including design. The framework can serve as a catalyst for future construction projects where SA systems are intended to be adopted at the design phase.

Designing the structure and architecture of situation-aware security information systems for residential complexes

Security information systems constitute a significant application domain for the concept of situational awareness. The object of this study is security information systems for residential complexes. The task addressed involved devsigning an efficient, flexible, and adaptive structure to ensure situational awareness in security information systems. Unlike existing systems, this structure is based on the integration of intelligent agents, server services, and a central unit that interacts with the Internet of Things (IoT) network. The proposed system ensures the autonomy of intelligent agents, which perform specialized tasks using integrated intelligent sensors, while server services handle basic computational tasks such as machine learning, pattern matching, and model construction. The central unit aggregates information, implements reasoning procedures, and identifies situations for the entire system. An architecture has been proposed that includes three main subsystems: video surveillance, access control, and operator service management. The essence of the results is the development of a flexible architecture that effectively combines IoT technologies with the situational awareness approach. The research results were achieved by integrating innovative approaches such as the use of intelligent agents, machine learning, and situational analysis, enabling a flexible distribution of functions among system components depending on the specific task requirements. The distinctive features of this architecture facilitate the implementation of the situational awareness principle and support continuous system learning processes. Given its modular architecture, the proposed system could be applied in extensive residential networks serviced by Internet providers, as well as in associations of co-owners of multi-apartment buildings. The formalization of architectural elements simplifies the process of designing and deploying systems, making them accessible for a wide range of applications in residential complexes by Internet service providers

Why is social media crucial for crisis communication in the Philippines? Exploring Facebook dynamics during natural disasters

The emergence of social media platforms has revolutionized communication dynamics during natural disasters, offering a lifeline for affected individuals. This study presents findings from an in-depth exploration of Facebook's role in crisis communication among individuals affected by natural disasters, particularly typhoons, in the Philippines. Through qualitative analysis rooted in phenomenology, the study illuminates the motivations, experiences and implications of user-driven content creation on Facebook during disasters. Key findings reveal that Facebook operates as a vital platform for communication, information sharing and support during crises. Participants actively engage in sharing updates, publishing content, exchanging feedback and utilizing private messaging to coordinate relief efforts and to express solidarity. These activities highlight Facebook's multifunctional role in crisis response, fostering community resilience and mutual aid. Moreover, the study identifies diverse motivations driving Facebook usage among disaster-affected individuals, including the need for emergency assistance, efficient communication, emotional support and situational awareness. Trust and verification also emerge as crucial factors, highlighting users' efforts to navigate the complex landscape of online information and to prevent misinformation dissemination.

Assessing Learning Outcomes in Simulation-based Education to Recognize and Respond to Deteriorating Patients in Nursing Education: A Scoping Review

Purpose : This scoping review examined the assessment of learning outcomes in simulation-based education to recognize and respond to deteriorating patients in nursing education. Methods : The review followed Arksey and O’Malley’s scoping review framework and the Joanna Briggs Institute’s manual. Studies were retrieved from databases such as Cochrane Central, PubMed, EMBASE, and the Cumulative Index to Nursing and Allied Health Literature. Results : A total of 15 studies, published between 2010 and 2023, were reviewed. Only six studies (40%) assessed both the cognitive learning outcomes related to recognition and the psychomotor outcomes related to responses to DPs. The learning outcomes included knowledge, situational awareness, cognition, the modified early warning score (MEWS), the situation–background–assessment–recommendation score, and teamwork in the cognitive domain; the MEWS action algorithm and psychomotor performance in the psychomotor domain; and self-efficacy, confidence, and self-confidence in the affective domain. Conclusion : Effective SBE for recognizing and responding to DPs should be designed to assess cognitive and psychomotor learning outcomes in nursing education. Future research should focus on enhancing non-technical skills through various approaches to SBE to recognize and respond to DPs.

간호대학생의 e-헬스 리터러시(인터넷 건강정보이해능력)가 정신건강증진행위에 미치는 영향

This study is a descriptive study conducted to identify the influence of e-health literacy on mental health promotion behaviors among nursing students. Data were collected from April to June 2023 from 248 nursing students in the first to fourth grades at a university in S-si, Gyeonggi-do. The e-health literacy was measured with a modified tool for eHEALS (eHealth Literacy Scale), and mental health promotion behavior was measured by modifying the situation awareness of the mental health tool. The data were analyzed using the SPSS WIN 29.0 Program, independent t-test and One-way ANOVA, Scheffé's test, Pearson correlation coefficient, and multiple regression analysis. As a result of the study, there were significant differences in mental health promotion behavior according to grade, self-perceived physical health status, self-perceived mental health status, coping strategy for mental stress, and health concerns. e-health literacy and mental health promotion behavior have a positive correlation (r=.38, p<.001). In the regression analysis, e-health literacy (β=.36, p<.001), second grade (β=.24, p<.001), first grade (β=.23, p<.001), health concern (β=.19, p=.001), coping strategy for mental stress with professional counseling (β=.17, p=.002), and conversation with friends (β=.15, p=.018) were followed, and these factors explained 29% of the variance. Therefore, to strengthen the mental health promotion behavior of nursing students, it is proposed to develop an education program that can increase the level of e-health literacy considering school years.

Research on Network Security Situational Awareness and Risk Assessment Model Based on Bayesian Network

With the rapid development of the information society, security threats in cyberspace are increasing day by day, posing severe challenges to national infrastructure, commercial operations, and even personal privacy. At present, the research of network security situational awareness and risk assessment model is faced with critical problems, such as significant demand for prior knowledge, high complexity of inference algorithm, insufficient dynamic adaptability, and inaccurate identification of risk categories. In view of this, this study proposes a new network security situational awareness and risk assessment model based on the Bayesian network, aiming to achieve timely early warning and accurate prediction of network threats through probability statistics methods. By comprehensively considering various heterogeneous data sources such as network traffic anomalies, system log anomalies, and external threat intelligence, we built a sizeable Bayesian network covering thousands of nodes and hundreds of thousands of edges to describe the occurrence mechanism and evolution path of network security incidents. Empirical research shows that the optimized model has an accuracy rate of 92%, a recall rate of 89%, and an F1 score of 90.5% on the test dataset, which is significantly better than the existing rule-based and machine-learning methods, especially when dealing with low-frequency threats with apparent long-tail effects, showing more robust adaptability and prediction accuracy. By dynamically monitoring the changing trend of network activities, we can identify potential risk points in advance, help take proactive protective measures before security threats occur, and effectively reduce economic losses caused by network intrusions. This study not only provides a brand-new theoretical framework and technical means for network security situational awareness and risk assessment but also opens up broad prospects for subsequent research directions and application scenarios.