Implementation Of Tool Research Articles

Emergency pediatric patients and use of the pediatric assessment triangle tool (PAT): a scoping review

BackgroundWe conducted a scoping review of the evidence for the use of the Pediatric Assessment Triangle (PAT) tool in emergency pediatric patients, in hospital and prehospital settings. We focused on the psychometric properties of the PAT, the reported impact, the setting and circumstances for tool implementation in clinical practice, and the evidence on teaching the PAT.MethodsWe followed the Joanna Briggs Institute methodology for scoping reviews and registered the review protocol. We searched MEDLINE, PubMed Central, the Cochrane Library, Epistemonikos, Scopus, CINAHL, Grey literature report, Lens.org, and the web pages of selected emergency pediatrics organizations in August 2022. Two reviewers independently screened and extracted data from eligible articles.ResultsFifty-five publications were included. The evidence suggests that the PAT is a valid tool for prioritizing emergency pediatric patients, guiding the selection of interventions to be undertaken, and determining the level of care needed for the patient in both hospital and prehospital settings. The PAT is reported to be fast, practical, and useful potentially impacting overcrowded and understaff emergency services. Results highlighted the importance of instruction prior using the tool. The PAT is included in several curricula and textbooks about emergency pediatric care.ConclusionsThis scoping review suggests there is a growing volume of evidence on the use of the PAT to assess pediatric emergency patients, some of which might be amenable to a systematic review. Our review identified research gaps that may guide the planning of future research projects. Further research is warranted on the psychometric properties of the PAT to provide evidence on the tool’s quality and usefulness. The simplicity and accuracy of the tool should be considered in addressing the current healthcare shortages and overcrowding in emergency services.Review registration: Open Science Framework; 2022. https://osf.io/vkd5h/

Scorecard Approach to Eliminate Onchocerciasis in Venezuela.

In the Americas, onchocerciasis has been eliminated in 11 of 13 endemic foci by mass administration of ivermectin. The remaining at-risk population resides in a contiguous cross-border transmission zone located in the Amazon jungle in northwest Brazil and southern Venezuela, known as the Yanomami Focus Area. Here, we describe the development and implementation of a data-driven tool, called the Scorecard Approach (SCA), for the 393 communities that comprise the Venezuela South Focus. The SCA was first applied in 2018 and is reassessed on an annual basis. This operational strategy seeks to prioritize communities with low ivermectin coverage while taking into account the nature and variation of other epidemiological and logistical variables. Numeric scores are assigned for each factor and added together to yield a composite score for each community that is categorized as high, medium, or low priority. In this way, the SCA serves as a valuable and comprehensive strategy for planning, monitoring, and maximizing programmatic efficiency. In addition, it has allowed the country to face the main challenges of this endemic area: its remoteness, its large areas of territory to cover, the semi-nomadic nature of the Yanomami people, and their continuous cross-border movements. For 2022, the SCA categorized 54 (13.7%), 108 (27.5%), and 231 (58.8%) communities as high, medium, and low priority, respectively. The results presented here show that prioritizing communities at risk and with greatest needs increases the feasibility of interrupting the transmission of onchocerciasis by 2025 in the last endemic focus in the Americas.

The Technological Past Informs the Present: A Conversation with Dr. Cynthia M. Okolo

Dr. Cindy Okolo is a professor emerita in the Department of Counseling, Educational Psychology, and Special Education at Michigan State University. Throughout her career, Dr. Okolo’s scholarship has focused on the academic and behavioral outcomes of students with disabilities through the implementation of technology in the classroom. Her work has involved the development and use of digital literacy tools, the development and implementation of virtual learning tools for teaching history and social studies, the exploration of universal design for learning (UDL), and the preparation of teachers to become technology leaders in education. Dr. Okolo’s research revolves around students with disabilities in middle school, particularly inclusive classrooms that include children and youth with and without disabilities.

Implementation of the Expert Nursing Standard: Caregivers' Oral Health Knowledge.

The promotion of oral health in nursing care is essential for preventing oral diseases and maintaining health in elderly vulnerable populations. There is a need for standardized guidelines and education. The aim of this study was to collect data on the attitudes and hopes of caregivers regarding the implementation of the German Expert Nursing Standard "Promotion of Oral Health in Nursing" (GENS-POHN) and to evaluate their oral healthcare knowledge before implementation. A cross-sectional study was conducted in five different care settings in Germany. A self-administered questionnaire was used to collect data on the attitudes and hopes of nursing assistants regarding the GENS-POHN. Oral healthcare knowledge was evaluated before implementation. Most participants had a positive attitude towards the GENS-POHN and hoped that its implementation would lead to greater safety and competence in daily oral healthcare tasks. Few participants currently use screening or assessment instruments for oral care. There is a need for further education and training, as well as the development and implementation of standardized guidelines and tools for screening and assessment, in oral care. The GENS-POHN as an expert standard could be made accessible to an international audience by translating it into other respective national languages, thereby enhancing its usability for a wider range of users.

Productivity improvement in the Manufacturing Industry through The Implementation of Lm Tools

Lean manufacturing is a set of principles and practices that may improve a company's efficiency and competitiveness in the marketplace. Lean manufacturing aims to maximize efficiency and productivity without compromising on product quality. Quality improvement is crucial since it reduces expenses by eliminating defective products. When production times are lowered, associated labor and infrastructure costs per unit are lowered, too. The elimination of unnecessary steps and processes is fundamental to the lean manufacturing philosophy. This might streamline, speed up, and enhance the process as a whole. Many companies have found success with lean manufacturing because it allows them to achieve their productivity targets and more by using straightforward, repeatable processes. Therefore, quality improves, production increases, and costs decrease. Participants were asked to rate the effectiveness of the implementation of these initiatives. After averaging the means across all scales, statistical analyses may be performed.

Navigating AI-Powered Personalized Learning in Special Education: A Guide for Preservice Teacher Faculty

Integrating Artificial Intelligence-Powered Personalized Learning (AI-PPL) in special education teacher preparation represents a shift toward tailoring educational experiences to meet the unique needs of preservice teachers and students with disabilities. This article explores the implementation of AI-PPL tools in teacher preparation programs, highlighting their potential to customize learning experiences, provide adaptive feedback, and enhance engagement through interactive content. This review of current AI-PPL functionalities, such as adaptive learning environments and customized feedback mechanisms, demonstrates how AI-PPL can impact teaching practices and student learning outcomes. The article introduces critical attributes for successful AI-PPL integration, such as ensuring accessibility and inclusivity. It calls for further professional development to enhance educator competency and skills. By presenting real-world examples and guiding questions for special education faculty, the authors offer practical insights for educators and faculty members to effectively navigate the complexities of adopting AI technologies in teacher preparation programs.

Evaluation of the accuracy and readability of ChatGPT-4 and Google Gemini in providing information on retinal detachment: a multicenter expert comparative study

BackgroundLarge language models (LLMs) such as ChatGPT-4 and Google Gemini show potential for patient health education, but concerns about their accuracy require careful evaluation. This study evaluates the readability and accuracy of ChatGPT-4 and Google Gemini in answering questions about retinal detachment.MethodsComparative study analyzing responses from ChatGPT-4 and Google Gemini to 13 retinal detachment questions, categorized by difficulty levels (D1, D2, D3). Masked responses were reviewed by ten vitreoretinal specialists and rated on correctness, errors, thematic accuracy, coherence, and overall quality grading. Analysis included Flesch Readability Ease Score, word and sentence counts.ResultsBoth Artificial Intelligence tools required college-level understanding for all difficulty levels. Google Gemini was easier to understand (p = 0.03), while ChatGPT-4 provided more correct answers for the more difficult questions (p = 0.0005) with fewer serious errors. ChatGPT-4 scored highest on most challenging questions, showing superior thematic accuracy (p = 0.003). ChatGPT-4 outperformed Google Gemini in 8 of 13 questions, with higher overall quality grades in the easiest (p = 0.03) and hardest levels (p = 0.0002), showing a lower grade as question difficulty increased.ConclusionsChatGPT-4 and Google Gemini effectively address queries about retinal detachment, offering mostly accurate answers with few critical errors, though patients require higher education for comprehension. The implementation of AI tools may contribute to improving medical care by providing accurate and relevant healthcare information quickly.

Improving Pain Management in the Intensive Care Unit by Assessment

PurposePatients in the intensive care unit suffer from pain caused by life-threatening illness or injury but also treatments such as surgery and nursing procedures such as venipuncture. Unconsciousness following head trauma or sedation stage complicates self-report, and both under- and over-management of pain can occur. Inadequate assessment and treatment might follow from unsuitable pain assessment practices. The aim of this study was to evaluate the effect of the implementation of a pain assessment tool on nurses` documentation of pain and the administration of analgesia and sedation. DesignQuantitative pre-post design. MethodsThe study was conducted at one intensive care unit at a university hospital and involved 60 patient records and 30 pre-implementations and 30 post-implementations of the Critical-Care Pain Observation Tool (CPOT). ResultsAfter implementation, a 38% adherence rate was found. The frequency of nurses’ pain evaluations increased significantly from 1.3 to 2.3 per nursing shift. The implementation of CPOT also improved how often nurses identified pain by use of facial expressions, muscle tension, and cooperation with the mechanical ventilator, whereas focus on vital signs dropped (p = .014). A larger proportion of patients (17%) received paracetamol after the CPOT implementation compared with before (8%). Findings were statistically significant at p < .01. ConclusionsImplementation of CPOT increased the frequency of pain evaluations, and the observable patient behavior was more often interpreted as pain-related. Nurses’ adherence rate to sustained patient behavior focus being modest highlights the essential need for ongoing improvements in practice. Implementation of a new tool must be followed by non-pharmacological and pharmacological pain management steps. Clinical ImplicationsImplementing the CPOT as a pain assessment tool has the potential to enhance assessment practices. However, it is important to note that simply increasing assessment frequency does not guarantee nursing interventions to alleviate pain. This indicates the need for additional steps to be taken in order for nurses to complete the pain assessment cycle and effectively address interventions and reassessments.

Identification and Management of Dental Anxiety by New Zealand Dentists.

More than 1 in 8 New Zealand (NZ) adults are dentally anxious, which can lead to avoiding dental care and a higher risk of poor oral health. However, little is known about how dentally anxious patients are identified and managed by NZ general dentists. This survey aimed to investigate how NZ dentists identify and manage dentally anxious patients. We conducted an email survey of NZ dentists in 2022, obtaining 212 responses. Along with demographic information, respondents were queried about whether they ask patients about past/current dental fears and their likely origin, how they assessed those fears, their usual management of dentally anxious patients, and how the management of dentally anxious patients could be improved. Almost three-quarters reported personally asking patients about past and/or current dental fears, and half enquired about bad life experiences that had led to those fears. Only 6 respondents (2.8%) reported using a formal dental anxiety/phobia assessment tool prior to treatment. For managing severely anxious adult dental patients, all dentists used at least 1 pharmacologic or psychological technique or referral to a colleague. The study identified several weaknesses among NZ dentists in identifying and managing dental anxiety patients. The use of formal dental anxiety/phobia assessment tools prior to treatment needs improvement. Addressing dental anxiety is a complex issue that requires a multipronged approach involving improved education, the development and implementation of better assessment tools, and a greater understanding of how dentists' current assessment and management of dental anxiety can be improved.

203 Healthcare professional and commissioners’ perspectives on the factors facilitating and hindering the implementation of digital tools for self-management of long-term conditions within UK healthcare pathways

203 Healthcare professional and commissioners’ perspectives on the factors facilitating and hindering the implementation of digital tools for self-management of long-term conditions within UK healthcare pathways

Sustainable Green Construction Practices Using GRIHA Parameters and BIM tools Implementation on Building Design

Sustainable Green Construction Practices Using GRIHA Parameters and BIM tools Implementation on Building Design

Survey of Multiple Destination Route Discovery Protocols

Route discovery protocols for multiple destination is one of the most interesting research topics since it is applied for real-world applications and needed in smart cities services such as: delivery services. The inclusion of artificial intelligence can improve the performance of multiple destination route discovery protocols. In this paper, we studied and analyzed multiple destination route discovery protocols based on different search strategies especially artificial intelligent methods. The survey compares between multiple destination route discovery protocols relate to its applications and implementation tools.

Design and development of a motion activated internet protocol video surveillance system for crowd monitoring

Internet Protocol (IP) cameras are powerful tools in security and crowd monitoring implementation owing to their efficient communication over a wide geographical area. However, for any authorized personnel to initiate recording based on an event, to report a security breach, or even to stop recording when an uninteresting scene is presented, such would have to sit at the reach of the control which is not always possible. In this proposal, we implement a motion activated internet protocol (MAIP) based video surveillance system using network video management for crowd monitoring. The system can activate itself to initiate video recording on detecting motion or event using its in-built features of the network cameras and Video Management Software (VMS). The system will result in an effective and efficient motion detection video surveillance with necessary features that allow for quick recording, conserved bandwidth, greater storage, space conservation, reduces CPU load on recording servers and also allows for integration with other systems.

Optimizing Cross-Functional Teams in Remote Work Environments for Product Development

Remote work settings have significantly increased in the current product development landscape. This change requires a reassessment of the operational, communication, and collaborative methodologies of cross-functional teams in order to guarantee successful product results. It is crucial to optimise these teams in distant environments in order to sustain production, creativity, and cohesiveness. This study investigates methods and optimal approaches to improve the effectiveness of cross-functional teams involved in remote product development.The first part analyses the distinct obstacles encountered by cross-functional teams operating remotely, such as deficiencies in communication, disparities in time zones, and the possibility of diminished team unity. This underscores the need of developing explicit procedures for virtual communication, including frequent video conferences, asynchronous updates, and collaborative platforms that enable immediate interactions and exchange of documents. This research subsequently examines the function of technology in enhancing the efficiency of distant cross-functional teams. It underscores the importance of implementation of strong project management tools and platforms that facilitate the monitoring of tasks, allocation of resources, and management of milestones. In addition, the use of sophisticated communication technologies, including as video conferencing, instant messaging, and virtual whiteboards, being explored as a method to improve immediate cooperation and collaborative problem-solving.

Evaluating English Teachers’ Artificial Intelligence Readiness and Training Needs with a TPACK-Based Model

With the rapid development and widespread adoption of artificial intelligence (AI) tools, the implementation of instructional pedagogy has transformed significantly. English teachers need to understand how AI tools can improve their teaching and must acquire the necessary technical and pedagogical knowledge to effectively utilize AI technology. Although the integration of AI into language teaching shows potential benefits, there remains a dearth of comprehensive research on English teachers’ perceptions, readiness, and professional development requirements in relation to AI.To address these knowledge research gaps, our study aims to evaluate English teachers’ current understanding of AI tools and their training needs for integrating AI into the English language classroom. Our proposed model uses the technological pedagogical content knowledge (TPACK) framework, which incorporates English language teaching and information literacy contexts. This framework allows for a holistic assessment of teachers’ readiness for integrating AI within English language teaching practices.A study was conducted with a class of preservice English teachers in Hong Kong. An online survey was designed to assess the readiness of English teachers for applying AI tools in the classroom as well as their understanding and level of information literacy. This study helped identify and address potential issues with the survey before launching it to a wider audience. Our findings confirmed the validity and reliability of the instrument and indicated that preservice English teacher participants are generally prepared to integrate AI tools into the English classroom. Corelation analysis was also conducted to assess the relationships among the constructs and showed that technological pedagogical knowledge (TPK) and instructional literacy (IL) were significant predictors of the overall TPACK construct. The study suggested professional training in the selection, implementation and progress monitoring of specific AI tools for English Language teaching; pedagogy design; and the ability to search for appropriate resources for the English classroom. The framework can be enhanced by using a mixed-method approach and incorporating a qualitative study to triangulate the findings. An explanatory sequential design will be recommended to collect quantitative data first, then qualitative data will be collected for further analysis.

The ERMES chatbot: A conversational communication tool for improved emergency management and disaster risk reduction

The increased occurrence and severity of worldwide disasters, exacerbated by the impact of climate change, pose significant challenges to emergency management, calling for novel and more effective Disaster Risk Reduction (DRR) approaches. Despite the phenomenological differences of diverse hazards and the heterogeneity of local policies and governance structures, effective communication systems are needed to better manage the available resources in all phases of the emergency management cycle, especially in the case of cross-border events. In this work, we present the design, implementation, and validation of a novel tool for emergency management, i.e., the ERMES Chatbot: a mobile-based conversational communication system developed to facilitate real-time bidirectional communication between control centres, in-field forces, and citizens. The methodology used to create the ERMES Chatbot is grounded on the user-centred design approach, which entails end-user involvement in all key phases of the development, including the definition of the end-user requirements, the technical design, and the final validation of the proposed solution. The co-design approach involved several organisations belonging to the DRR domain, which includes a gamified experience for citizens and is iteratively validated through four in-field demonstration events based on realistic emergency scenarios with the involvement of emergency practitioners, volunteering organisations, and citizens.

Body Image Perception and Social Support Are Important Predictors of Quality of Life in Bladder Cancer Patients after Cystectomy with Urinary Diversion

Introduction: Systematic evaluations focusing on the perception of body image and social support in relation to quality of life (QoL) outcomes in patients radical cystectomy (RC) with urinary diversion (UD) are currently lacking. This study investigated the relationship between body image perception, social support, and QoL in bladder cancer patients who underwent RC with UD. Methods: A cross-sectional survey was conducted using validated general oncology tools to assess QoL in relation to newly implemented tools assessing body image perception and social support. Body image perception was assessed with the Self-Image Scale, and social support was assessed using the Illness-Specific Social Support Scale. Logistic regression models were used to analyze factors associated with QoL and body image, respectively. Results: The survey revealed a significant association of body image perception with QoL, as well as social support with body image perception. This is the first study to systematically evaluate these psychosocial factors in the context of QoL for RC patients, highlighting their critical role in patient-reported outcomes. Conclusion: Body image perception and social support are important psychosociological factors that affect QoL of bladder cancer patients post-RC. Targeted psychosocial interventions could be promising for improving QoL patients post-RC.

Assessment tools for evaluating the efficiency of practices to control food safety performance indicators in cereal-based small-medium scale food manufacturing establishments in Bangladesh

Safe production in small-medium enterprises (SMEs)-based food processing industries is a challenge in developing countries due to limited resources and inefficient process control activities. For the development of the situations, we first need to identify the context characteristics and control activities that have an impact on the safety of the finished products. In the present study, a comprehensive target-oriented tool was designed to evaluate the efficiency of control practices with respect to contextual factors to understand the likelihood of common hazards in cereal-based small and medium factories. The identified 18 control activities, based on previous studies, were assigned to three food safety performance indicators, such as allergen contamination, pesticide residue or heavy metal contamination, and fungal contamination. The performance level of activities is a marker of whether the control practices are able to control the food safety performance indicators in cereal-based SME manufacturers. A Venn diagram is used to visually present the efficiency of control activities. Moreover, among the 18 control practices, 7 for mitigating pesticide residues or heavy metal contamination, 9 for allergen control, and 13 control practices for fungal contamination were identified. As comparatively lower control practices (water source, raw material control, testing, etc.) are involved in mitigating pesticide residues or heavy metal contamination, which proves context factors (Good Agricultural Practices, contamination-free soil, etc.) are more important to minimize the risk. We inspected the implementation of the developed tool in 44 cereal-based small-medium manufacturers in Bangladesh and calculated 59.06% efficiency in controlling fungal contamination. Most of the cereal-based SMEs in Bangladesh operate from a poor to a basic level, which is an indication of the high likelihood of occurring hazards.

Strategies for Error Reduction: Why More Stringent Premarket Evaluations Do Little to Prevent Laboratory Errors and Traffic Accidents

Laboratory testing is a complex process with a significant error rate. Studies of laboratory errors have found that the major causes are preanalytical factors, interferences, and process errors. Efforts by regulatory agencies to improve quality via more stringent premarket evaluations of laboratory tests therefore have poor prospects of reducing laboratory errors and improving test quality. Efforts toward increasing the regulation of laboratory tests are analogous to preventing traffic accidents by increasing the premarket evaluation of automobiles. This analogy illustrates how increased premarket evaluation has limited prospects for quality improvement and, in some cases, actually contributes to errors and lower quality. Tools that are used by laboratories to detect, prevent, and address analytical errors are discussed, and the increased implementation of such tools offers approaches that can be used to improve laboratory quality.

Innovative methods for integrating translation memory and CAT tools: Enhancing intelligent support in human translation processes

This paper explores the innovative integration of Translation Memory (TM) and Computer-Assisted Translation (CAT) tools to enhance translation efficiency, consistency, and quality in multinational organizations. By adopting a user-centric interface design, modular system architecture, and cloud-based deployment, the integrated system addresses diverse translation needs while ensuring data security and privacy. Key features include real-time translation suggestions powered by machine learning algorithms, seamless access to TM databases, and real-time collaboration tools. The paper discusses implementation strategies, challenges, and solutions, highlighting the importance of user training and continuous improvement. A case study demonstrates significant improvements in translation speed, accuracy, and user satisfaction, underscoring the potential of advanced translation technologies to transform translation workflows. The findings provide valuable insights into best practices for successful implementation and optimization of TM and CAT tools in complex, large-scale environments.