Scaling Options Research Articles

Online anatomy education during the Covid-19 pandemic: Opinions of medical, speech therapy, and BSc Anatomy students.

With the emergence of the Covid-19 pandemic in 2020, it was difficult to predict if the "cadaveric-based (golden) standard" of teaching anatomy would be possible in the unforeseeable future. This forced traditional anatomical teaching and learning practices to be transitioned to remote online platforms. This study explored the opinions of anatomy students (n=51), on their online learning experience of anatomy during the Covid-19 pandemic. A mixed methods approach using a descriptive, exploratory study design was conducted, by use of an online survey. The survey consisted of a six-point Likert scale and was assembled into four sub-categories. Likert scale options ranged from; strongly disagree, to strongly agree, and not applicable. Results obtained seem to tally with expectations, indicating an adequate theoretical course component with room to improve practical online teaching. Most participants had a positive perception of the theoretical course content, duration, and platforms of communication. Virtual classes were simple to navigate with few technical difficulties experienced by the participants. Students also noted having access to sufficient study material, videos, and additional online material. Overall, more than half of all participants reported adapting well to the remote learning environment, however, the greatest challenge experienced highlighted a sense of deprivation from the lack of cadaver exposure and hands-on instruction. This research highlighted the effects of the pandemic on the modality of anatomy education and how it affected students. Although anatomy is multi-modal, it can be concluded that it is possible to achieve academic success by using online learning methods.

Novel evolved Yarrowia lipolytica strains for enhanced growth and lipid content under high concentrations of crude glycerol

BackgroundYarrowia lipolytica is a well-studied oleaginous yeast known for its ability to accumulate and store intracellular lipids, while growing on diverse, non-conventional substrates. Amongst them, crude glycerol, a low-cost by-product of the biodiesel industry, appears to be an interesting option for scaling up a sustainable single-cell oil production process. Adaptive laboratory evolution (ALE) is a powerful tool to force metabolic adaptations endowing tolerance to stressful environmental conditions, generating superior phenotypes with industrial relevance.ResultsY. lipolytica MUCL 28849 underwent ALE in a synthetic medium with increasing concentration of pure or crude glycerol as a stressing factor (9–20% v/v) for 520 generations. In one case of pure glycerol, chemical mutagenesis with ethyl methanesulfonate (EMS) was applied prior to ALE. Growth profile, biomass production and lipid content of 660 evolved strains (EVS), revealed 5 superior isolates; exhibiting from 1.9 to 3.6-fold increase of dry biomass and from 1.1 to 1.6-fold increase of lipid concentration compared to the parental strain, when grown in 15% v/v crude glycerol. NGS for differential gene expression analysis, showed induced expression in all EVS affecting nucleosomal structure and regulation of transcription. As strains differentiated, further changes accumulated in membrane transport and protein transport processes. Genes involved in glycerol catabolism and triacylglycerol biosynthesis were overexpressed in two EVS. Mismatches and gaps in the expressed sequences identified altered splicing and mutations in the EVS, with most of them, affecting different components of septin ring formation in the budding process. The selected YLE155 EVS, used for scale-up cultivation in a 3L benchtop bioreactor with 20% v/v crude glycerol, achieved extended exponential phase, twofold increase of dry biomass and lipid yields at 48 h, while citric acid secretion and glycerol consumption rates were 40% and 50% lower, respectively, compared to the parental strain, after 24 h of cultivation.ConclusionALE and EMS-ALE under increasing concentrations of pure or crude glycerol generated novel Y. lipolytica strains with enhanced biomass and lipid content. Differential gene expression analysis and scale-up of YLE155, illustrated the potential of the evolved strains to serve as suitable “chassis” for rational engineering approaches towards both increased lipid accumulation, and production of high-added value compounds, through efficient utilization of crude glycerol.

A Comparative Analysis of Biodegradation and Bioconversion of Lentinula edodes and Other Exotic Mushrooms.

Mushrooms are capable of bioconverting organic residues into food. Understanding the relationship between high-quality yields and substrate biomass from these residues is critical for mushroom farms when choosing new strains. The objective of this exploratory study was, therefore, to analyze whether exotic mushrooms, namely, Pleurotus eryngii, Flammulina velutipes, and Agrocybe aegerita, could biologically convert the substrate into edible mushrooms as effectively as Lentinula edodes (baseline). Five experiments were carried out. Biological efficiency, biodegradability coefficient, mass balance and chemical characterization of the substrate were evaluated. Strategically hydrating the sawdust enabled L. edodes to achieve the greatest biodegradability and biological efficiency of 0.5 and 94.2 kg dt-1, respectively. The values for L. edodes on wheat straw without hydration were 0.2 and 68.8 kg dt-1, respectively. From 1000 kg of fresh substrate, P. eryngii produced 150.1 kg of edible mushrooms, making it technically competitive with L. edodes on wheat straw (195.9 kg). Hence, P. eryngii was the most reliable option for scaling among the exotic mushrooms. The analytical insights from our study provide further knowledge to advance the field's prominence in high-throughput mushroom-producing systems, particularly for exotic mushrooms.

Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation

Models of socio-environmental or social-ecological systems (SES) commonly address problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders. In SES modelling multiple interactions occur on different scales among various phenomena. These scale phenomena include the technical, such as system variables, process detail, inputs and outputs, which most often require spatial, temporal, thematic and organisational choices. From a good practice and project efficiency perspective, the problem scoping and conceptual model formulation phase of modelling is the one to address well from the outset. During this phase, intense and substantive discussions should arise regarding appropriate scales at which to represent the different phenomena. Although the details of these discussions influence the path of model development, they are seldom documented and as a result often forgotten. We draw upon personal experience with existing protocols and communications in recent literature to propose preliminary guidelines for documenting these early discussions about the scale(s) of the studied phenomena. Our guidelines aim to aid modelling group members in building and capturing the richness of their rationale for scoping and scale decisions. The resulting transcripts are intended to promote transparency of modelling decisions and provide essential support for the justification of the final model for its intended use. They also facilitate adaptive modifications of the pathway of model development via retracing decisions and iterative reflection upon alternative scale options.

Using a consensus meeting to enhance fracture care education in low income countries

BackgroundA key strategy to building surgical capacity in low income countries involves training care providers, particularly in the interventions highlighted by the Lancet Commission for Global Surgery, including the management of open fractures. This is a common injury, especially in areas with a high incidence of road traffic incidents. The aim of this study was to use a nominal group consensus method to design a course on open fracture management for clinical officers in Malawi.MethodsThe nominal group meeting was held over two days, including clinical officers and surgeons from Malawi and the UK with various levels of expertise in the fields of global surgery, orthopaedics and education. The group was posed with questions on course content, delivery and evaluation. Each participant was encouraged to suggest an answer and the advantages and disadvantages of each suggestion were discussed before voting through an anonymous online platform. Voting included use of a Likert scale or ranking available options. Ethical approval for this process was obtained from the College of Medicine Research and Ethics Committee Malawi and the Liverpool School of Tropical Medicine.ResultsAll suggested course topics received an average score of greater than 8 out of 10 on a Likert scale and were included in the final programme. Videos was the highest ranking option as a method for delivering pre-course material. The highest ranking methods for each course topic included lectures, videos and practicals. When asked what practical skill should be tested at the end of the course, the highest ranking option was “initial assessment”.ConclusionThis work outlines how a consensus meeting can be used to design an educational intervention to improve patient care and outcomes. Through combining the perspectives of both the trainer and trainee, the course aligns both agendas so that it is relevant and sustainable.

Ultrasonic and Impact-Echo Testing for the Detection of Scaling in Geothermal Pipelines

The efficiency and longevity of components in geothermal plants are significantly reduced by mineral deposition in pipes, also known as scaling [1]. A number of methods are used to monitor fouling (a broader term for all types of organic and inorganic deposition) in other industries, such as the oil, gas and food industries. These include direct and indirect, offline, in-situ and online, as well as inline methods, each of which have pros and cons [2, 3]. An effective monitoring solution specific to the high temperature conditions in geothermal plants, which optimises maintenance and cleaning measures in dependency of scaling, has yet to be developed. In this paper, two non-destructive testing techniques: contact ultrasonic testing (UT) and impact-echo (IE) testing are investigated in their viability as methods to detect scaling growth in geothermal plants. A descaling measurement was conducted on a heavily scaled segment of an obsolete pipeline from the production well of the geothermal power plant in Sauerlach, Germany. The pipeline segment was inserted in a test rig and the scaling was gradually etched away using an acidic solution. At regular time intervals, the scaling thickness was measured mechanically and contact UT as well as IE measurements were carried out. The testing apparatus was designed to withstand high temperatures ({140},^{circ }{text {C}} at the inlet pipe surface) and to be easy to install whilst being cost-efficient. Both techniques yielded usable results with submillimeter resolution. The advantages and limitations of the two methods are discussed. Impact-echo testing, in particular, can be automated and presents a simple and cost-efficient scaling monitoring option.

The economics of global green ammonia trade – “Shipping Australian wind and sunshine to Germany”

This paper contributes to understanding the transformation of global energy trade to green energy carriers, focusing on green ammonia as the foreseeable first green hydrogen carrier. We provide a comprehensive overview of today's ammonia trade and assess scaling options for the trade of green ammonia. To that aim, we develop an optimization model for the integrated assessment of the green ammonia value chain that covers all steps from green ammonia production in an exporting country, up to delivery to a harbor in an importing country. The model endogenously chooses among different technology options and determines cost minimal operation. In a case study, we apply the model to the large-scale import of ammonia from Australia to Germany in a scenario for 2030. The results show that green ammonia can reach cost parity with gray ammonia even for moderate gas prices (but not necessarily with blue ammonia) if CO2 prices are high enough. We also provide a sensitivity analysis with respect to the interest rate and other key technical and economic parameters and show that cracking ammonia to provide pure hydrogen comes at a 45% cost markup per MWh at the destination.

Understanding Training Needs in Pediatric Feeding for Allied Health Professionals: An Australian Perspective.

Clinician experience and confidence can negatively impact pediatric feeding service availability, but limited research has investigated what training allied health professionals (AHPs) need to increase these factors. This study developed and distributed a survey investigating Australian AHPs' self-reported confidence and anxiousness, training needs, factors impacting training access, and training preferences. This study was conducted over two phases. Phase 1 involved development and refinement of the survey, and Phase 2 involved distribution to Australian AHPs. Questions pertained to general demographics, feeding experience, feeding confidence and skills perception, and training needs. The questions were composed of multiple-choice, Likert scale, and short-response options. Overall, 198 complete responses were received. Participants reported significantly lower confidence and higher anxiousness working with infants compared to older children (p < .01). Increased frequency of service provision predicted higher self-reported confidence and lower anxiousness (p < .01). Practical training opportunities including case discussion, videos, and clinical feedback were preferred. Access facilitators were online, on-demand training; however, respondents reported preferring hands-on training opportunities. Common barriers included cost, time, competing professional development priorities, and distance/travel. Findings have highlighted that recency and frequency of practice impact self-reported confidence and anxiousness, and that AHPs self-report lowest confidence and highest anxiety working with infants compared to older age groups. Overall, the findings highlight the need for flexible, practical, and remotely accessible training opportunities, as well as the need for access to regular clinical supervision and a pediatric feeding caseload.

Outcomes of intervention treatment for concurrent cardio-cerebral infarction: a case series and meta-analysis

Background: The concurrent occurrence of acute ischemic stroke and acute myocardial infarction is an extremely rare emergency condition that can be lethal. The causes, prognosis and optimal treatment in these cases are still unclear. Methods: We conducted the literature review and 2 additional cases at Al-Shifa Hospital, we analyzed clinical presentations, risk factors, type of myocardial infarction, site of stroke, modified ranking scale and treatment options. We compare the mortality rate among patients with combination intervention treatment (both percutaneous coronary intervention for coronary arteries and mechanical thrombectomy for cerebral vessels) and medical treatment at the hospital and 90 days after stroke. Results: In addition to our cases, we identified 94 cases of concurrent cardio-cerebral infarction from case reports and series with a mean age of 62.5 ± 12.6 years. Female 36 patients (38.3%), male 58 patients (61.7%). Only 21 (22.3%) were treated with combination intervention treatment. The mortality rate at hospital discharge was (33.3%) and the mortality rate at 90 days was (49.2%). In patients with the combination intervention treatment group: the hospital mortality rate was 13.3% and the 90-day mortality rate was: 23.5% compared with the mortality rate in medical treatment (23.5% at the hospital and 59.5% at 90 days (p value 0.038 and 0.012 respectively) Conclusion: Concurrent cardio-cerebral infarction prognosis is very poor, about a third of patients died before discharge and half of the patients died 90 days after stroke. Despite only one-quarter of patients being treated by combination intervention treatment, this treatment modality significantly reduces the mortality rate compared to medical treatment.

TRANSLATING CORE VALUES INTO ACTIONABLE STRATEGIES

TRANSLATING CORE VALUES INTO ACTIONABLE STRATEGIES

Dying in hospital-staff perceptions on providing quality care.

To understand what healthcare staff perceive contributes to the quality of patient and family/whānau experiences of dying and death on a hospital inpatient ward. A survey was created, piloted and sent to all staff members who had cared for a deceased patient within two working days of their death, at Christchurch Hospital (CH), New Zealand. The survey comprised questions evaluating whether the patients physical, emotional, social or family/whānau needs were met, using both a Likert scale and free-text options. The survey was sent over a three-month period in 2016/2017. A total of 169 staff responded to the deaths of 51 patients. The majority (71.3%) of staff agreed that "end-of-life care was of a high standard", with the physical symptoms domain holding the highest score for both agreement (68%) and disagreement (13%) that "physical symptoms were well managed". Qualitative analysis of free-text responses revealed three themes: coordinated care (service delivery, complex case or communication needs, teamwork); culture of practice (dignity, trust, respect and relationships); and complexity of care (encompassing complex physical symptoms or patient or family/whānau interpersonal dynamics). Evaluation of quality of death in hospitals can be enhanced by routine use of surveys of staff who cared for the deceased person. Such surveys could comprise part of a suite of tools to provide a holistic view of dying and death, complementing methods such as retrospective audits and family/whānau interviews.

Actionable Policy Options for Scaling-Up System of Rice Intensification for Ensuring Higher Productivity, Energy Efficiency and Sustainable Rice Production

Globally, India stands first in rice area and second in rice production. To feed the growing population, rice production has to be increased amid strong competition for limited resources including land. Also, concerns have been raised about yield gaps in rice. The system of rice intensification is one of the strategies to narrow the yield gaps. Rice is the major crop in India, therefore, the identification of an energy-efficient rice cultivation system is important to food security and sustainable intensification (SI). Hence, a comparison was made between conventional and the system of rice intensification (SRI) methods of rice cultivation by conducting two experiments. One field experiment was conducted from 2013 to 2017 at 25 locations across India under the All India Coordinated Rice Improvement Project and another experiment was conducted in 2017 using surveys by collecting data from 262 randomly selected SRI farmers using a personal interview method in the Telangana state of India. The 5-year experimental data revealed that the SRI method of cultivation produced higher rice grain yield (up to 55%) compared to the conventional transplanting method. Survey data revealed that total costs of rice production reduced by 22.71% under SRI. Break even output under SRI was reduced by 58.1%. Adoption of SRI saved total energy inputs by 4350 MJ/ ha. The energy productivities were 0.16 kg/MJ and 0.21 kg/MJ for conventional and SRI methods, respectively. Therefore, for ensuring higher productivity, net returns, energy efficiency and sustainable rice production it is recommended to adopt an environmentally friendly SRI method of crop establishment in the Telangana region of India. Based on the constraints as perceived by the farmers, policy options for scaling up of SRI are suggested.

Comparative Analysis of Scalability Approaches using Data Mining Methods on Health Care Datasets

The primary issue in data analysis is scalability of data mining methods. Various scaling options have been explored in prior research to overcome this problem. Several scaling strategies are explored and tested on various datasets in this research. The cascade scaling method is proposed to improve the efficacy of existing methods. The proposed method starts with gathering a huge dataset and then pre- processed. Once the dataset has undergone pre-processing, it is spitted into smaller subsets of equal size to apply a data mining strategy on each subset. The outcomes of the data mining approach on all subsets are pooled and aggregated for the final results. The accuracy of the given algorithm is used to evaluate its performance. The proposed method and existing methods are evaluated on two health care datasets: PIMA Indian Diabetes and Heart Disease. On the basis of the Data mining methods the proposed scaling approach reflects better results as compared to the existing scaling approaches. On both datasets, the proposed method is compared to previous work published by different authors in earlier studies. It was discovered that the proposed method outperformed previous research. For a few data mining methods, the proposed method achieves 100 percentage accuracy.

Using Rasch measurement theory to explore the fitness for purpose of the genetic counseling outcome scale: a tale of two scales.

The genetic counseling outcome scale (GCOS-24) is commonly used in clinical genetics to measure patient empowerment; however, there is inconclusive psychometric evidence about this scale. Using data from an urban Canadian clinic where the GCOS-24 is routinely administered before (T1) and 1month after (T2) genetic counseling, we used Rasch measurement theory (RMT) to test the ordering of response option thresholds, fit, spread of item locations, residual correlations, person separation index (PSI), and stability across time. Data from 379 participants showed that the original GCOS-24 items had poor fit to the Rasch model (χ2 = 367.8, p < 0.001). Two models emerged that demonstrated excellent fit to the Rasch model. In Model 1, the response scale options were collapsed and 8 items were removed, leading to an excellent fit to the Rasch model (χ2 = 112.4, df = 144, p = 0.975), good reliability (rp = 0.82), and responsiveness to change (mean = 0.75 logits, F = 125.68, p < 0.001). In Model 2, the response scale options were collapsed, 3 items were removed, and the scale divided into two sets (GCOS-Pos, GCOS-Neg). The GCOS-Pos set showed excellent overall fit to the Rasch model (χ2 = 92.5, df = 90, p = 0.407), good reliability (rp = 0.73), and responsiveness to change (mean = 0.74 logits, F = 80.12, p < 0.001). The GCOS-Neg set showed excellent overall fit to the Rasch model (χ2 = 84.55, df = 97, p = 0.81), but poor reliability (rp = 0.19) and small, but significant responsiveness to change (mean = 0.19 logits, F = 28.73, p < 0.001). These models show that there are psychometric issues with the GCOS-24 scale, and our study provides options for how to measure empowerment more robustly.

The Role of Parallelism in the Evolution of Optical Fiber Communication Systems

In order to overcome the capacity limitations of current lightwave systems based on the single-mode optical fiber, massively parallel transmission in the spatial domain [space-division multiplexing (SDM)] supported by extended parallelism in the frequency domain (ultrawideband (UWB) systems) must be used. This article reviews key aspects of parallel transmission systems as the only significant capacity scaling option going forward and discusses the various tradeoffs on an architectural level and a hardware integration level. In doing so, this article also serves as an introduction to the more detailed accounts of fiber-optic systems and their future scaling within this Special Issue of the Proceedings of the IEEE.

An investigation into the soft skills required of potential building graduate employee for sustainable employment

This study investigated the soft skills that Building Technology Students need for sustainable employment in Building Construction Industry. The study answered four research questions and tested four null hypotheses at 0.05 level of significance. The study adopted descriptive survey research design and was carried out in South-West, Nigeria. The population for the study was of 197 comprising of 159 employers from registered building construction industry and 38 building technology teachers from Building Technology Department in Polytechnics in South-West, Nigeria. There was no sampling for the study since the entire population was used. The instrument that was used for collecting data for the study was a structured questionnaire. The questionnaire was divided into two parts, I and II. Part I contains items that elicited the demographic information of the respondents while part II contains 62 soft skills items in four sections (A, B, C and D) on a five point likert-type rating scale option of Extremely Needed (EN),Somewhat Needed (SN), Neither Needed or Not Needed (NN), Somewhat Not Needed (SN) and Extremely Not Needed (EN) with a corresponding value of 5, 4, 3, 2 and 1 respectively. The face validation of the instrument was carried out by five experts. The Cronbach alpha coefficient (∝) method was used to ascertain the internal consistency of the questionnaire items and it yielded an overall reliability coefficient of 0.88. Data generated from the administration of the questionnaire was analyzed with Statistical Package for Social Sciences (SPSS) using mean and t-test statistics to answer the research questions and hypotheses respectively at 0.05 level of significance. Findings revealed that personal-attribute skills, people-related skills, higher-order thinking skills and career-attribute skills are required by building technology students in Polytechnics for sustainable employment in building construction industry. Based on the findings of the study, appropriate conclusions and recommendations were made which include the integration of the identified soft skills into the curriculum of building technology programme in Polytechnic among others.

An High Accuracy Lung Cancer Detection System Using MRMR Method

Lung cancer is one of the main cause of the death and health issue in many countries with 5-year survival rate of only10–16%. In this project we use machine learning algorithms to diagnose a cancer and start treatment in early stages. MRMR method and decision tree algorithms to predict the high accuracy of the cancer. In this project we use scikit-learn libraries like sklearn and pandas to predict and classify the dataset of the lung cancer patients. Slicing the dataset and feature scaling options are used to train the dataset. After that we use confusion matrix , f1 score and accuracy score to predict the accuracy of the result.Success obtained was 99.51% with 200 features provided by MRMR. In the dataset lung cancer.csv the result attributes which have 0 value which represent person have no lung cancer and 1 value represents person have lung cancer. These researchers then performed the 10- fold cross-validation for model evaluation.IOT arduino UNO is interfaced with WIFI module to collect the data. wifi sensor is connected with various IOT sensor to obtain the information of the patient like temp, BP, Pulse rate..Using wifi module patient data is transfer to doctor to protect the patient in early stages.

Determination of foliar traits in an ecologically distinct conifer species in Maine using Sentinel-2 imagery and site variables: Assessing the effect of leaf trait expression and upscaling approach on prediction accuracy

Leaf traits are expressed either as area-based content (g m−2) or mass-based concentration (mg/g or %) and subsequently scaled to canopy level using leaf area index (LAI) and foliage biomass, respectively. Despite their wide use, it remains unclear whether the two trait expressions and scaling options (by LAI or foliage biomass) yield the same prediction accuracy using multispectral remote sensing data and additional site variables. In this study, we used LAI (m2 m−2) and foliage biomass (kg) to upscale area-based content [leaf mass per area (LMA), equivalent water thickness (EWT), nitrogen (Narea) and potassium (Karea)] and mass-based concentration [leaf dry matter content (LDMC), leaf water content (LWC), Nmass, and Kmass)], respectively in two contrasting study sites (coastal vs inland) for an ecologically important yet distinct regional species (red spruce, Picea rubens Sarg.) in Maine, USA. We used partial least squares regression (PLSR) and random forest (RF) to examine the effect of these metrics on model performance and prediction accuracy at both leaf- and canopy-scales using Sentinel-2 satellite bands, vegetation indices, as well as several topographical variables and depth to water table (DWT). The best-performing models (based on cross-validated normalized root mean square error: nRMSE) were used to generate high-resolution canopy trait maps. Results demonstrated that prediction accuracies of area-based leaf traits were generally higher (R2 = 0.41–0.65, nRMSE = 0.14–0.20) than the mass-based concentration (R2 = 0.42–0.65, nRMSE = 0.15–0.25) for both sites and modelling techniques. We also observed that canopy traits upscaled by LAI yield better prediction accuracies (R2 = 0.44–0.70, nRMSE = 0.17–0.20) compared to a foliage biomass upscaling approach (R2 = 0.41–0.57, nRMSE = 0.19–0.24). Among site variables, DWT was a significant variable in modeling canopy traits and showed robust behavior across the contrasting study sites. Overall, our study highlights the importance of trait expression and how it affects foliar trait retrieval accuracy at both leaf- and canopy-scale using satellite multispectral data and site variables. These findings have implications on leaf trait modelling especially in the context of monitoring dynamics in forest health and productivity from space.

Faculty perceptions on one-best MCQ development.

The aim of this study was to determine the perception of faculty of undergraduate medical and dental programmes in various private and public sector institutes regarding their Readiness, Attitude and Institutional support for developing high-quality one-best MCQs. A validated questionnaire was designed for recording demographic data and responses related to Readiness, Attitude and Institutional support based on 5-point Likert scale and multiple options. Scores for items on Likert scale were categorised (Readiness: poor 0-12, good 13-24, Attitude: negative 0-12, positive 13-24, Institutional support: no support 0-12, highly supportive 13-24). The individual and overall scores related to Readiness, Attitude and Institutional support were compared to demographic characteristics using Independent samples and Paired samples t-test as appropriate. Data was analysed using SPSS version 25.0. P-value of <0.05 (two-sided) was considered significant. With a response rate of 87.5%, the mean scores for Institutional support were higher (14.45 ± 4.73) compared to those for Readiness (13.39 ± 4.51) and Attitude (12.54 ± 4.59). Responses to multiple choice items revealed that faculty considered MCQ writing workshops to be effective while facing most difficulty in formulating scenario and homogenous options. Most faculty reported no commitment issues but desired on-job protected time for item development. No significant association was found between the scores and age group, gender, qualification, institute type, department and designation of participants. Overall, the faculty were found to be motivated and committed to developing high-quality one-best MCQs. With continued institutional support, faculty can be expected to further engage in writing such items.

Regional adaptation of the education in palliative and end-of-life Care Pediatrics (EPEC-Pediatrics) curriculum in Eurasia.

Pediatric palliative care (PPC) is a priority to improve pediatric hematology oncology (PHO) care in Eurasia. However, there are limited regional opportunities for PPC education. We describe the adaptation and implementation of a bilingual end-user Education in Palliative and End-of-Life Care (EPEC)-Pediatrics course for PHO clinicians in Eurasia. Due to COVID-19, this course was delivered virtually, consisting of prerecorded, asynchronous lectures, and a bilingual workshop with interactive lectures and small group sessions. A pre-postcourse design was used to evaluate the knowledge acquisition of the participants including their knowledge alignment with World Health Organization (WHO) guidance, ideal timing of palliative care, and comfort in providing palliative care to their patients. Questions were mostly quantitative with multiple choice or Likert scale options, supplemented by free-text responses. A total of 44 (76%) participants from 14 countries completed all components of the course including pre- and postcourse assessments. Participant alignment with WHO guidance improved from 75% in the pre- to 90% in the postcourse assessments (p < 0.001). After participation, 93% felt more confident controlling the suffering of children at the end of life, 91% felt more confident in prescribing opioids and managing pain, and 98% better understood how to hold difficult conversations with patients and families. Most participants (98%) stated that they will change their clinical practice based on the skills and knowledge gained in this course. We present a successful regional adaptation of the EPEC-Pediatrics curriculum, including novel delivery of course content via a virtual bilingual format. This course resulted in significant improvement in participant attitudes and knowledge of PPC along with an understanding of the ideal timing of palliative care consultation and comfort in providing PPC to children with cancer. We plan to incorporate participant feedback to improve the course and repeat it annually to improve access to high-quality palliative care education for PHO clinicians in Eurasia.