Case Scenario Research Articles

Cost-effectiveness analysis of procalcitonin and lung ultrasonography guided antibiotic prescriptions in primary care.

Antimicrobial resistance comes with high morbidity and mortality burden, and ultimately high impact on healthcare and social costs. Efficient strategies are needed to limit antibiotic overuse. This paper investigates the cost-effectiveness of testing patients with lower respiratory tract infection with procalcitonin, either at the point-of-care only or combined with lung ultrasonography. These diagnostic tools help detect the presence of bacterial pneumonia, guiding prescription decisions. The clinical responses of these strategies were studied in the primary care setting. Evidence is needed on their cost-effectiveness. We used data from a cluster-randomized bi-centric clinical trial conducted in Switzerland and estimated patient-level costs using data on resource use to which we applied Swiss tariffs. Combining the incremental costs of the two strategies and the reduction in the 28-days antibiotic prescription rate (APR) compared to usual care, we calculated Incremental Cost-Effectiveness Ratios (ICER). We also used the Cost-Effectiveness Acceptability Curve as an analytical decision-making tool. The robustness of the findings is ensured by Probabilistic Sensitivity Analysis and scenario analysis. In the base case scenario, the ICER compared to usual care is $2.3 per percentage point (pp) reduction in APR for the procalcitonin group, and $4.4 for procalcitonin-ultrasound combined. Furthermore, we found that for a willingness to pay per patient of more than $2 per pp reduction in the APR, procalcitonin is the strategy with the highest probability to be cost-effective. Our findings suggest that testing patients with respiratory symptoms with procalcitonin to guide antibiotic prescription in the primary care setting represents good value for money.

The important role of distortion recognition in student advocacy leadership development.

Though promoting student advocacy has become an essential part of leadership education, few studies explore development of advocacy in leadership education. This article offers how distortions, an aspect of a Black feminist reframing of dissonance, is related to existing leadership education literature. It then introduces students' voices demonstrating the importance of the realization of distortions in student advocacy development and links distortions with how power communicates and upholds systemic oppression. Finally, we offer practical recommendations based on a case scenario that utilize Black feminist perspectives of dissonance in refining student advocacy leadership education. Such insight prompts more effective strategies in student advocate development.

Designing, piloting and evaluating (through a matched pre- and post-implementation survey) a targeted e-learning resource on antimicrobial resistance for public health professionals.

Antimicrobial resistance (AMR) is a significant global public health threat and key priority for the public health, especially health protection, workforce to lead by example. There is a paucity of learning resources on this for public health professionals (PHPs) in the UK. This project aimed to develop and disseminate a tailored interactive learning resource and evaluate impact on self-reported intention to change behaviour. Learning objectives were agreed, content developed by the multi-disciplinary team and piloted by PHPs in 2022 alongside a matched pre- and post-implementation evaluation survey. Questions were mapped to the capability-opportunity-motivation-behaviour change model. Before and after responses were calculated to compare change in self-reported knowledge, understanding and behaviour. Significance of change in binary responses was estimated. The resource was delivered using an interactive, user-friendly and cost-free internal platform. Thirty-one PHPs completed the pilot e-learning and survey. Perceived and actual knowledge increased in parallel. Actual knowledge on AMR burden increased from 6.45 to 35.48% (P = 0.004). Self-reported confidence to explain AMR to others improved by 0.71 (95% CI; 0.38-1.04: P = 0.0001) Likert points on a five-point scale. Motivation to advocate for antimicrobial stewardship (AMS) in day-to-day work, improved by 0.71 (95% CI; 0.34-1.08: P < 0.00001) Likert points. Case scenarios were well-received as an effective way to apply theory to practice. Ensuring a well-informed and confident public health workforce is vital for reducing the AMR threat and advocating for AMS with the public and partner organizations. This targeted e-learning module is an effective additional learning medium in contributing to PHPs knowledge, understanding and self-reported intention to change behaviours.

An example of leveraging AI for documentation: ChatGPT-generated nursing care plan for an older adult with lung cancer.

Our article demonstrates the effectiveness of using a validated framework to create a ChatGPT prompt that generates valid nursing care plan suggestions for one hypothetical older patient with lung cancer. This study describes the methodology for creating ChatGPT prompts that generate consistent care plan suggestions and its application for a lung cancer case scenario. After entering a nursing assessment of the patient's condition into ChatGPT, we asked it to generate care plan suggestions. Subsequently, we assessed the quality of the care plans produced by ChatGPT. While not all the suggested care plan terms (11 out of 16) utilized standardized nursing terminology, the ChatGPT-generated care plan closely matched the gold standard in scope and nature, correctly prioritizing oxygenation and ventilation needs. Using a validated framework prompt to generate nursing care plan suggestions with ChatGPT demonstrates its potential value as a decision support tool for optimizing cancer care documentation.

Polycyclic aromatic hydrocarbon skin permeation efficiency in vitro is lower through human than pigskin and decreases with lipophilicity.

Polycyclic aromatic hydrocarbons (PAH) are persistent environmental pollutants, which occasionally appear as contaminants in consumer products. Upon dermal contact, transfer of PAH into the stratum corneum (s.c.) and migration through the skin may occur, resulting in this class of highly toxic compounds to become bioavailable. In this study, dermal penetration through human and porcine skin of 24 PAH, comprising broad mass (152-302 g/mol) and octanol-water partition coefficient (logP: 3.9-7.3) ranges, was evaluated via Franz diffusion cell in vitro assays. More lipophilic and potentially more toxic PAH had decreased permeation rates through the rather lipophilic s.c. into the more hydrophilic viable (epi-)dermis. Furthermore, human skin was less permeable than pigskin, a commonly used surrogate frequently applied in skin penetration studies. In particular, the s.c. of human skin retains a greater share of PAH, an effect that is more pronounced for smaller PAH. Moreover, we compared the skin permeation kinetics of different PAH in pigskin. While small PAH (< 230 g/mol, logP < 6) permeate the skin quickly and are detected in the receptor fluid after 2 h, large PAH (> 252 g/mol, logP ≥ 6) do not fully permeate the skin up to 48 h. This indicates that highly lipophilic PAH do not become bioavailable as readily as their smaller congeners when transferred to the skin surface. Our data suggest that pigskin could be used as a surrogate for worst case scenario estimates of dermal PAH permeation through human skin.

ACT To Sustain: Adoptive Cell Therapy To Sustain access to non-commercialized genetically modified cell therapies.

Genetically modified cell therapies (GMCT), particularly immune effector cells (IEC) such as chimeric receptor antigen (CAR) T cells, have shown promise in curing cancer and rare diseases after a single treatment course. Following close behind CAR T approvals are GMCT based on hematopoietic stem cells, such as products developed for hemoglobinopathies and other disorders. Academically sponsored GMCT products, often developed in academic centers without industry involvement, face challenges in sustaining access after completion of early phase studies when there is no commercial partner invested in completing registration trials for marketing applications. The American Society for Transplantation and Cellular Therapy (ASTCT) formed a task force named ACT To Sustain (Adoptive Cell Therapy to Sustain) to address the "valley of death" of academic GMCT products. This paper presents the task force's findings and considerations regarding financial sustainability of academically sponsored GMCT products in the absence of commercial development. We outline case scenarios illustrating barriers to maintaining access to promising GMCT developed by academic centers. The paper also delves into the current state of GMCT development, commercialization, and reimbursement, citing examples of abandoned products, cost estimates associated with GMCT manufacturing and real-world use of cost recovery. We propose potential solutions to address the financial, regulatory, and logistical challenges associated with sustaining access to academically sponsored GMCT products and to ensure that products with promising results do not languish in a "valley of death" due to financial or implementational barriers. The suggestions include aligning US Food and Drug Administration (FDA) designations with benefit coverage, allowing for cost recovery of certain products as a covered benefit, and engaging with regulators and policy makers to discuss alternative pathways for academic centers to provide access. We stress the importance of sustainable access to GMCT and call for collaborative efforts to develop regulatory pathways that support access to academically sponsored GMCT products.

Assessing the suitability of desalination techniques for hydraulic barriers

Seawater intrusion is a worldwide increasing challenge, which lowers the freshwater availability by salination of fresh groundwater resources in coastal areas. The abstraction-desalination-recharge (ADR) methodology can combat seawater intrusion, whereby desalination is hereby the key factor for the overall efficiency of aquifer remediation. Which desalination technique is suitable within ADR depends on several factors and was not discussed before. We use a multi-criteria decision analysis and cost analysis to compare nanofiltration, reverse osmosis, electrodialysis, and (membrane) capacitive deionization and show for three case scenarios which desalination technique is most suitable within ADR. Overall, electrodialysis, nanofiltration, and reverse osmosis have shown the best utility value for saline groundwater salinity of 1–10 g L−1, whereby electrodialysis is more suitable for lower salinities. The lowest desalination costs are calculated for nanofiltration and reverse osmosis with 0.3–0.6 € m−3 depending on specific energy costs. Even capacitive deionisation can be a suitable alternative for low, slightly saline groundwater (1 g L−1) if the technology readiness level and a lifetime of electrodes increase and material costs decrease. These new insights provide a data analysis, costs, and decision support for desalination which are needed for the holistic approach to counteract seawater intrusion.

Implementation of team based learning for MBBS students – An innovative teaching learning method in medical education

Team-Based Learning (TBL) is an educational approach that enhances student engagement through individual assessments and collaborative group work. It is an effective and structured form of small group learning adaptable to large classroom settings. TBL ensures student accountability through various stages, including pre-class preparation, readiness assurance tests, problem-solving exercises, and immediate feedback. This study aims to implement and assess the efficacy of the TBL strategy among MBBS students in a large group teaching environment. The pilot study adopted a TBL approach, involving steps such as pre-class preparation with PDF materials and a WhatsApp video guide issued a week prior, individual and team readiness assurance tests (iRAT and tRAT) conducted via Google Forms and hard copy MCQs, clarification sessions on MCQs and relevant medical topics, and collaborative learning through case scenarios related to Type 2 diabetes. Discussions and conclusions were facilitated by the faculty, followed by immediate and scheduled feedback using Google Forms. Statistical analysis was performed using an unpaired t-test to compare iRAT and tRAT scores. The study gathered 133 responses from the first batch and 140 from the second batch of first year MBBS students. The analysis revealed significant improvements in scores from iRAT to tRAT, indicating the effectiveness of TBL in enhancing student learning outcomes. Feedback from the students showed high levels of engagement and interest in the learning process, with over 98% in both batches finding the TBL approach interesting and interactive. The findings suggest that TBL is a valuable and effective educational strategy that improves learning outcomes and fosters collaborative learning among students.

An extended graphical solution for undrained cylindrical cavity expansion in K0‐consolidated Mohr–Coulomb soil

AbstractThis paper develops a general and complete solution for the undrained cylindrical cavity expansion problem in nonassociated Mohr‐Coulomb soil under nonhydrostatic initial stress field (i.e., arbitrary values of the earth pressure coefficient), by expanding a unique and efficient graphical solution procedure recently proposed by Chen and Wang in 2022 for the special in situ stress case with . It is interesting to find that the cavity expansion deviatoric stress path is always composed of a series of piecewise straight lines, for all different case scenarios of K0 being involved. When the cavity is sufficiently expanded, the stress path will eventually end, exclusively, in a major sextant with Lode angle θ in between and or on the specific line of . The salient advantage/feature of the present general graphical approach lies in that it can deduce the cavity expansion responses in full closed form, nevertheless being free of the limitation of the intermediacy assumption for the vertical stress and of the difficulty existing in the traditional zoning method that involves cumbersome, sequential determination of distinct Mohr–Coulomb plastic regions. Some typical results for the desired cavity expansion curves and the limit cavity pressure are presented, to investigate the impacts of soil plasticity parameters and the earth pressure coefficient on the cavity responses. The proposed graphical method/solution will be of great value for the interpretation of pressuremeter tests in cohesive‐frictional soils.

Protecting digital rights of India: planning for succession at Internet Freedom Foundation (IFF)

Learning outcomes The learning objectives of this case study are based on Bloom’s taxonomy. Upon completion of the case study discussion and exercises, successful students will be able to design a leadership transition and succession plan for non-profit organisations; identify and evaluate critical skills and competencies required in leadership positions; and frame expectations and responsibilities for new and departing executives. Case overview/synopsis Apar Gupta co-founded Internet Freedom Foundation (IFF), a digital rights organisation born out of SaveTheInternet – Net Neutrality movement of 2015, credited for urging the Telecom Regulatory Authority of India to uphold net neutrality in India. And ban zero-cost internet services that promoted data discrimination in the country. After working on and winning the net neutrality movement, Gupta identified many areas in technology where democratic rights had not been identified or were yet to be clearly defined (like in the case of net neutrality). There was also a service gap between the existing internet volunteer groups and digital rights organisations, which could IFF fill. This was to provide objective clarity, stakeholder identification, handle policy discussions and, most importantly, arrange resources to support movements over the long term. This prompted him to co-found IFF in 2017, which he later joined as a full-time executive director in 2018. IFF worked at the intersection of technology, democratic rights and government policies and was comparable to some global organisations, such as the Electronic Frontier Foundation in the USA and the Open Rights Group in the UK. Still, none existed in India at the time. After four years as a full-time executive director in 2022, he was convinced that it was finally time for him to act on the pre-defined strategic departure plan and work towards succession for the executive director position. While there were visible gaps in the system, Gupta’s leadership design and plans had helped IFF overcome existential challenges in the past. Also, while digital rights were still at a nascent stage in emerging economies, under Gupta’s leadership, IFF had delivered unmatched value to its beneficiaries in the world’s biggest digital consumer market. However, constant changes in regulations and continuing financial constraints made him nervous about the outcomes of the succession and the overall sustainability of IFF. Gupta wanted to ensure that this phased transition from executive director after two years and then trustee manager after the next four years are carefully communicated to reduce the likelihood of attrition and loss of trust. Being the co-founder and the first and only executive director IFF had seen, the organisation would also require significant skill and competency mapping to identify the new executive leadership. But with no clear internal successor in sight, the non-profit trust would also need a successor who not only was competent but also would share a passion for the type of work done by IFF, its unique delivery mode, and also would openly inherit its position in society. The other alternative strategic routes present were to look for dual leadership or interim leadership, but then there could be concerns about Gupta’s influence overshadowing any such alternative. In the case scenario, IFF is planning for succession while navigating the organisation through financial constraints and constant regulatory changes to ensure long- and short-term sustainability. Complexity academic level The case study has been written to gain insights into departure-defined successive planning in non-profit organisations. The case study can also be used to gain insights into innovative start-ups and innovative non-profit start-ups, as digital rights are still at nascent stages in emerging markets. The case study will be valuable for courses such as human resource management, strategic human resource management, social entrepreneurial leadership, leadership development, start-up environment, innovation and entrepreneurship, public policy, development studies, cyber security and information technology. The case study also allows students and young professionals to take the perspective of an innovative start-up founder and design a departure-defined succession plan. The case study can also be useful for senior students wanting to undertake an entrepreneurial career by starting or joining a non-profit organisation. While the case study is suitable for postgraduate- and executive-level courses, it can also be used for conducting entrepreneurial workshops and skill training. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

Wind Power Integration and Challenges in Low Wind Zones. A Study Case: Albania

High wind performance systems are influenced by many factors such as site wind resources and configuration, technical wind turbine features and many financial conditions. Scenario planning and modelling activities often focus on restricted parameters and numbers to justify wind power plant performance. To better understand possible pathways to scaling up the distributed wind market in Albania, a deep and multidimensional calculations based on Monte Carlo analysis, using RETScreen and wind JEDI model, to assess socio-economic impact as a function of turbine output power, operating and maintenance cost and many other financial inputs by testing different WT (i.e., VESTAS, GAMESA, W2E and NORDEX) with rated power from 3.45 MW up to 4.5MW applied on LCOE, NPV, SPP, equity payback, B-C, after-tax IRR on equity and effects of GHG credits extended at a sensitivity range of ±35% is scientifically performed. From the simulation results LCOE reaches a minimal value of €43.48/MWh, if the debt rate is 99 % and a debt interest rate of 5.0%, a TotCapEx of €828/MW (-35 % less expenditures) indexed as the best scenario. For the base case scenario LCOE results €62.79/MWh, when applying a debt rate of 80% and a TotCapEx of (€1274/MW), while in the worst-case scenario LCOE impart a maximal value of €87.63/MWh if a TotCapEx of €1720/MW (+35 % more expenditures) and a share of 52 % debt rate is applied. Local annual economic impact (m€) during construction period and operating period evaluated in the wind JEDI model result around m€ 89.92 and m€ 23.54, respectively. As a conclusion, wind power plants (WPP), installed in low wind zones (Albania and many other EU countries) would be of interest if an electricity export rate of 110€/MWh, and a GHG credit rate of €50/tCO2 were accepted.

Pelvic inflammatory disease

Pelvic inflammatory disease (PID) is defined as infection-induced inflammation of the upper female genital tract. Infection is usually ascending from the lower genital tract and may involve any combination of endometritis, salpingitis, parametritis, tubo-ovarian abscess, and pelvic peritonitis. Young women under the age of 25 are more likely to develop PID, with most cases being caused by sexually transmitted infections such as Chlamydia trachomatis, Neisseria gonorrhoeae and Mycoplasma genitalium. Diagnosis is primarily clinical and can be difficult, with symptoms ranging from asymptomatic to serious illness, and may be non-specific. Early diagnosis and treatment can potentially prevent both short-term complications, including tubo-ovarian or pelvic abscess, and long-term complications, such as chronic pelvic pain, infertility and ectopic pregnancy. This article aims to discuss the clinical presentation, diagnosis and management using a clinical case scenario as an example within the primary care setting using the latest evidence available.

Financial Implications of Rooftop Solar Penetration in Sri Lanka from Utility Point of View

Solar is one of the fast growing and economical renewable power generation sources. The intention of development of solar power generation is to promote clean energy while addressing the basic requirement of uninterrupted and reliable electricity supply.The Sri Lankan government decided to adopt a policy that would use subsidies to encourage the growth of solar PV-based electricity. As a result, the market developed with a large number of customers eager to install solar rooftop systems, and they received strong assistance from solar power service providers. Hence, the utility is required to absorb the solar energy produced and this study focuses on the impact of solar penetration to the utility.System dispatch data for year 2019 and rooftop solar generation data for a period of 6 months of year 2019 were considered for the analysis in this paper. The model compares the financials of two scenarios to estimate the impact to the utility. The base case scenario, which is business as usual with the already installed solar generation in the system and No solar scenario which assumes that there is no solar in the system and therefore the demand is met by other available generation capacities in the system.This paper examines the two scenarios with careful calculations of how the system can still run without solar in the system. Daily demand patterns were also analysed and then expanded to months and summarized for the year. This research focuses the financial impact of solar electricity penetration to the national grid and how everyone can still be benefitted.

Artificial intelligence in practice: measuring its medical accuracy in oculoplastics consultations

Purpose: The aim of this study was to investigate the medical accuracy of responses produced by Chat Generative Pretrained Transformer 4 (Chat GPT-4) and DALLE-2 in relation to common questions encountered during oculoplastic consultations. Methods: The 5 most frequently discussed oculoplastic procedures on social media were selected for evaluation using Chat GPT-4 and DALLE-2. Questions were formulated from common patient concerns and inputted into Chat GPT-4, and responses were assessed on a 3-point scale. For procedure imagery, descriptions were submitted to DALLE-2, and the resulted images were graded for anatomical and surgical accuracy. Grading was completed by 5 oculoplastic surgeons through a 110-question survey. Results: Overall, 87.3% of Chat GPT-4’s responses achieved a score of 2 or 3 points, denoting a good to high level of accuracy. Across all procedures, questions about pain, bruising, procedure risk, and adverse events garnered high scores. Conversely, responses regarding specific case scenarios, procedure longevity, and proceduredefinitions were less accurate. Images produced by DALLE-2-were notably subpar, often failing to accurately depict surgical outcomes and realistic details. Conclusions: Chat GPT-4 demonstrated a creditable level of accuracy in addressing common oculoplastic procedure concerns. However, its limitations in handling case-based scenarios suggests that it is best suited as a supplementary source of information rather than a primary diagnostic or consultative tool. The current state of medical imagery generated by means of artificial intelligence lacks anatomical accuracy. Significant technological advancements are necessary before such imagery can complement oculoplastic consultations effectively.

Deep learning-based predictive models for pavement patching and manholes evaluation

ABSTRACT Deep Learning (DL) techniques have been applied to the processing and evaluation of pavement conditions. DL-based predictive models are rapid and have higher accuracy compared to traditional methods. In this research, some models were developed to appraise pavement patching by considering the severity and the manhole cover utilising images collected by the Road Surface Profiler (RSP) from Bus Rapid Transit (BRT) lines in Tehran, Iran. Two cases (scenarios) were regarded in this research: 1) Patching without considering the severity, and 2) Patching by considering the severity. YOLOv5, YOLOv6, and YOLOv7 as one-stage object detection algorithms, and Faster R-CNN (ResNet-50) and Faster R-CNN (MobileNet_v3) as two-stage object detection algorithms were evaluated to choose the desired algorithm. The results exhibited that the trained model on YOLOv5 has better performance and is faster than the rest of the algorithms. In addition, the influence of the classes’ combination on model performance was scrutinised. Based on the results of the other classes, the outcomes of the study suggested that the model can detect and train better when the model is trained by a dataset with all classes. Furthermore, the performance of the model was also investigated by examining the effect of image size and YOLOv5's architectures. Based on the obtained results, YOLOv5 and an image size of 640*640 outperformed the rest. In Case 1, the precision, recall, F1-score, and mAP were 75.8%, 67.4%, 71.35%, and 77.4%, respectively. Moreover, the values of these metrics in Case 2, were 70%, 61.2%, 65.3%, and 64.4%, respectively. Hence, the results demonstrated that the developed model can be used with high performance in the detection and evaluation of pavement patching by severity, and manholes in Pavement Management Systems (PMS) and maintenance and rehabilitation plans.

Enhancing Battery Capacity Estimation Accuracy through the Neural Network Algorithm

Accurate estimation of battery metrics, such as state of health (SOH), is crucial for effective battery management systems (BMS) due to capacity degradation over time. This paper proposes a methodology to enhance battery capacity estimation accuracy by addressing uncertainties related to state of charge (SOC) estimation and measurement. The methodology employs the Neural Network Algorithm (NNA), an optimization algorithm inspired by artificial neural networks (ANNs). The NNA generates an initial population of pattern solutions and iteratively updates them using a weight matrix, bias operator, and transfer function operator. By combining the advantages of ANNs and optimization techniques, the NNA aims to find an optimal solution considering interdependent variables and incorporating global and local feedbacks. Leveraging the capabilities of the NNA, our objective is to identify the candidate that minimizes a specified cost function, ensuring up-to-date cell capacity through a memory forgetting factor. The algorithm's precision was validated using NASA's Prognostic Data, demonstrating outstanding performance by surpassing two aggressive algorithms in terms of accuracy. In the most severe case scenario, the algorithm achieved a peak error of less than 0.4%. Furthermore, the algorithm consistently demonstrated predictive performance measures that were superior to those of the compared algorithms.

The DIKWP (Data, Information, Knowledge, Wisdom, Purpose) Revolution: A New Horizon in Medical Dispute Resolution

The doctor–patient relationship has received widespread attention as a significant global issue affecting people’s livelihoods. In clinical practice within the medical field, applying existing artificial intelligence (AI) technology presents issues such as uncontrollability, inconsistency, and lack of self-explanation capabilities, even raising concerns about ethics and morality. To address the problem of doctor–patient interaction differences arising from the doctor–patient diagnosis and treatment, we collected the textual content of doctor–patient dialogues in outpatient clinics of local first-class hospitals. We utilized case scenario analysis, starting from two specific cases: multi-patient visits with the same doctor and multi-doctor interaction differences with the same patient. By capturing the external interactions and the internal thought processes, we unify the external expressions and internal subjective cognition in doctor–patient interactions into interactions between data, information, knowledge, wisdom, and purpose (DIKWP) models. We propose a DIKWP semantic model for the doctor–patient interactions on both sides, including a DIKWP content model and a DIKWP cognitive model, to achieve transparency throughout the entire doctor–patient interaction process. We semantically–bidirectionally map the diagnostic discrepancy space to DIKWP uncertainty and utilize a purpose-driven DIKWP semantic fusion transformation technique to disambiguate the uncertainty problem. Finally, we select four traditional methods for qualitative and quantitative comparison with our proposed method. The results show that our method performs better in content and uncertainty handling. Overall, our proposed DIKWP semantic model for doctor–patient interaction processing breaks through the uncertainty limitations of natural language semantics in terms of interpretability, enhancing the transparency and interpretability of the medical process. It will help bridge the cognitive gap between doctors and patients, easing medical disputes.

A medical language for climate discourse

Innovative communication theories propose that we understand messages not by decoding their meaning but by inferring what speakers intend to express. However scientifically accurate the messages climate scientists have put forward, the appropriate inferences may not have been drawn by most of their audiences. One of the main reasons may be that scientific metaphors allow for multiple interpretations, yet, because of their expressive power, they impact discourses disproportionately. Climate communication took a path of euphemistic scientific expressions partially due to the noble scientific norms of self-restraint and modesty, but the hidden implications of climate jargon distort the way non-experts think about the heating climate. Consequently, the current climate jargon hinders informed decisions about Earth’s life support systems. Changing the softened expressions of climate language, from the cool of basic research to the heat and compassion of medical contexts, may allow for more productive public and political debates – which may lead to more powerful policy solutions. Speaking and thinking in medical terms could turn the perception of worst case scenarios from hypotheticals or doomism to life-saving interventions. We typically start reducing fever before it gets out of control, let alone crosses a threshold of potential death. Instead of putting on a positivist mascara, a calm and serious discussion of safety measures in medical terms, for example, talking about climatic tipping cascades as metastases, could foster a more honest evaluation of the required legal and regulatory steps to keep our home planet habitable.

Barriers to implementing problem-based learning at the school of medicine of Debre Berhan University, Ethiopia

BackgroundImplementing PBL in teaching and learning can be challenging due to a variety of complex barriers. Studies on barriers to the implementation of problem-based learning in Ethiopia are scarce. This study aimed to explore the barriers to the implementation of problem-based learning at the Debre Berhan University Medical School.MethodsA qualitative study was conducted among faculty and medical students at the medical school. Purposive sampling was used to select participants. Semi-structured interviews were conducted with tutors and academic leaders, including the problem-based learning coordinator, the biomedical sciences coordinator, and the school dean. Data was also collected from students through focus group discussions. All interviews and discussions were recorded. The four steps of data analysis of Spradley, including domain analysis, taxonomic analysis, componential analysis, and theme analysis, were employed.ResultsThe study identified student-related, tutor-related, case scenario-related, and assessment-related barriers as the most significant obstacles to implementing problem-based learning. These barriers included work overload for both students and tutors, lack of training and experience among tutors, student reluctance, absence of standardized case scenarios, subjectivity of assessment methods, and on-the-spot assessment of students.Conclusions and recommendations: Lack of both tutor and student commitment, lack of standardized cases, absence of a recognition of staff input, gap in communication skills, work overload, lack of continuous training, and at-spot evaluation of students were identified as the main barriers to the implementation of PBL.

Deriving Manageable Transdisciplinary Research Models for Complicated Problematics Associated with Next-Generation Cyber-Physical Systems: Part 2 - Elaboration and Deployment

This second Part of the paper (i) develops a detailed procedural model for handling complicated research problematics, (ii) transfers the procedural framework into a scenario of processing steps, (iii) demonstrates the deployment of the procedural scenario in a sample case, and (iv) addresses some important issues of research model development for supradisciplinary research. First, the framework called Holistic Systematic Combinatorial Scoping (HSCS) is introduced that comprises 21 subsequent activity steps. To illustrate the practical application of the HSCS framework, a demonstrative case study of preventing frequently occurring accidents at an uncontrolled intersection is presented. This case-study explains how the HSCS framework can facilitate (i) semantic capturing and rendering of complicated research problematics, (ii) scoping the overall research problematics and constructing definitive research problematics, and (iii) deriving a manageable research model of definitive research problematics. Further research intends to test the methodology by transdisciplinary research collectives and other CPSs related problematics.