Learning assessment

AIM: This study aimed to compare the level of cultural competence among nurses working in clinical practice in Slovakia and the Czech Republic. BACKGROUND: Demographic changes have greatly affected the health sector in Slovakia and the Czech Republic. By identifying the level of nurses' cultural competence, many of the complications encountered in caring for patients from different cultures can be avoided. However, few studies have explored the cultural competence of nurses in clinical practice in these countries...

OBJECTIVES: The aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo. METHODS: Multimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup...

Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early-intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD)...

Accurate atom mapping, which establishes correspondences between atoms in reactants and products, is a crucial step in analyzing chemical reactions. In this paper, we present a novel end-to-end approach that formulates the atom mapping problem as a deep graph matching task. Our proposed model, AMNet (Atom Matching Network), utilizes molecular graph representations and employs various atom and bond features using graph neural networks to capture the intricate structural characteristics of molecules, ensuring precise atom correspondence predictions...

BACKGROUND: A number of recommendations for the teaching of biostatistics have been published to date, however, student opinion on them has not yet been studied. For this reason, the aim of the manuscript was to find out the opinions of medical students at universities in Poland on two forms of teaching biostatistics, namely traditional and practical, as well as to indicate, on the basis of the results obtained, the related educational recommendations. METHODS: The study involved a group of 527 students studying at seven medical faculties in Poland, who were asked to imagine two different courses...

BACKGROUND: Artificial intelligence (AI) tools are designed to create or generate content from their trained parameters using an online conversational interface. AI has opened new avenues in redefining the role boundaries of teachers and learners and has the potential to impact the teaching-learning process. METHODS: In this descriptive proof-of- concept cross-sectional study we have explored the application of three generative AI tools on drug treatment of hypertension theme to generate: (1) specific learning outcomes (SLOs); (2) test items (MCQs- A type and case cluster; SAQs; OSPE); (3) test standard-setting parameters for medical students...

BACKGROUND: The study aimed to assess the impact of different training modalities on otoscopy performance during a practical exam using a high-fidelity simulator and to determine if objective evaluation of otoscopy is feasible using a simulator that records insertion depth and tympanic membrane coverage. METHODS: Participants were assigned to one of four groups: control and three intervention groups with varying training approaches. Participants received otoscopy training and then were assessed through a practical exam on a high-fidelity simulator that uses virtual reality to visualize the ear canal and middle ear...

BACKGROUND: Point-of-care ultrasound (POCUS) is becoming increasingly crucial in the Pediatric Emergency Department for objective patient examination. However, despite its growing interest and wide-ranging applications, POCUS remains relatively unexplored in general pediatric training and education. Many physicians still find it challenging to comprehend and implement. METHODS: A theoretical-practical POCUS course for pediatric residents was conducted at the University of Catania, Italy...

BACKGROUND: The integration of Objective Structured Clinical Examinations (OSCEs) within the professional pharmacy program, contributes to assessing the readiness of pharmacy students for Advanced Pharmacy Practice Experiences (APPEs) and real-world practice. METHODS: In a study conducted at an Accreditation Council for Pharmacy Education (ACPE)-accredited Doctor of Pharmacy professional degree program, 69 students in their second professional year (P2) were engaged in OSCEs...

BACKGROUND: Although game-based applications have been used in disaster medicine education, no serious computer games have been designed specifically for training these nurses in an IEMT setting. To address this need, we developed a serious computer game called the IEMTtraining game. In this game, players assume the roles of IEMT nurses, assess patient injuries in a virtual environment, and provide suitable treatment options. METHODS: The design of this study is a retrospective comparative analysis...

BACKGROUND: The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease. METHODS: We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46-68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers...

BACKGROUND: Road traffic accidents (RTAs) are predicted to become the world's seventh leading cause of death by 2030. Given the significant impact of RTAs on public health, effective hospital preparedness plays a pivotal role in managing and mitigating associated health and life-threatening issues. This study aims to meticulously evaluate the preparedness of selected hospitals in western Iran to handle road traffic accidents with mass casualties (RTAs-MC). METHODS: The study employed a descriptive-analytical approach, utilizing a reliable and valid questionnaire to measure hospitals' preparedness levels...

BACKGROUND: Work-integrated learning (WIL) is widely accepted and necessary to attain the essential competencies healthcare students need at their future workplaces. Yet, competency-based education (CBE) remains complex. There often is a focus on daily practice during WIL. Hereby, continuous competency development is at stake. Moreover, the fact that competencies need to continuously develop is often neglected. OBJECTIVES: To ultimately contribute to the optimization of CBE in healthcare education, this study aimed at examining how competency development during WIL in healthcare education could be optimized, before and after graduation...

BACKGROUND: Accurately deciphering clonal copy number substructure can provide insights into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles has become an effective means to unmask intra-tumor heterogeneity (ITH). However, copy numbers inferred from single-cell DNA sequencing (scDNA-seq) data are error-prone due to technically confounding factors such as amplification bias and allele-dropout, and this makes it difficult to precisely identify the ITH...

BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. We aimed to develop a multi-outcome deep learning model using CT multi-level body composition parameters to detect metabolic syndrome (MS), osteoporosis and sarcopenia by identifying metabolic clusters simultaneously. We also investigated the prognostic value of metabolic phenotyping by CT model for long-term mortality. METHODS: The derivation set (n = 516; 75% train set, 25% internal test set) was constructed using age- and sex-stratified random sampling from two community-based cohorts...

BACKGROUND: Machine learning (ML) models are evaluated in a test set to estimate model performance after deployment. The design of the test set is therefore of importance because if the data distribution after deployment differs too much, the model performance decreases. At the same time, the data often contains undetected groups. For example, multiple assessments from one user may constitute a group, which is usually the case in mHealth scenarios. METHODS: In this work, we evaluate a model's performance using several cross-validation train-test-split approaches, in some cases deliberately ignoring the groups...

Road damage is a great threat to the service life and safety of roads, and the early detection of pavement damage can facilitate maintenance and repair. Street view images serve as a new solution for the monitoring of pavement damage due to their wide coverage and regular updates. In this study, a road pavement damage dataset, the Street View Image Dataset for Automated Road Damage Detection (SVRDD), was developed using 8000 street view images acquired from Baidu Maps. Based on these images, over 20,000 damage instances were visually recognized and annotated...

This study begins by considering the resource-sharing characteristics of scientific research projects to address the issues of resource misalignment and conflict in scientific research project management. It comprehensively evaluates the tangible and intangible resources required during project execution and establishes a resource conflict risk index system. Subsequently, a resource conflict risk management model for scientific research projects is developed using Back Propagation (BP) neural networks. This model incorporates the Dropout regularization technique to enhance the generalization capacity of the BP neural network...

BACKGROUND: Malignant Gastric Outlet Obstruction (mGOO) has been standardly treated by surgical Gastrojejunostomy (S-GJ) or Endoscopic Stenting (ES). Recently, EUS-Gastrojejunostomy (EUS-GJ) has emerged as an alternative, despite its worldwide diffusion is heterogeneous. The aim of this survey was to assess clinical decision-making around mGOO and to explore current opinions regarding EUS-GJ. METHODS: An online survey, spread through social networks and EPC newsletter, was created exploring opinions regarding indications, contraindications, benefits/risks, availability of mGOO treatments; 2 case vignettes explored clinical decision-making in different scenarios...

To evaluate user perceptions and educational impact of gamified online role-play in teledentistry as well as to construct a conceptual framework highlighting how to design this interactive learning strategy, this research employed an explanatory sequential mixed-methods design. Participants were requested to complete self-perceived assessments toward confidence and awareness in teledentistry before and after participating in a gamified online role-play. They were also asked to complete a satisfaction questionnaire and participate in an in-depth interview to investigate their learning experience...