Assessment Tool Research Articles

On the transcreation, format and actionability of healthcare translations

In public-health crises, members of multilingual communities must be able to access, understand, trust and act upon behaviour-change messaging. The role of translators is therefore critical, not only for the relaying of information but also in the transcreation of texts, understood as adaptation to suit the characteristics of an intended audience. Failure to use transcreation may produce messaging that is culturally inappropriate and thus ineffective. This study analyses healthcare resources created by governments in Australia with a view to identifying formatting and other visual features that would benefit from transcreation. A mixed-method approach combined numerical evaluation of four documents using the Patient Education Materials Assessment Tool (PEMAT) and a bottom-up thematic analysis of the way the same texts were discussed by 58 members of a broad range of ethnocultural and linguistic groups in Victoria, Australia. The findings point to a need to go beyond the linguistic aspects of the translation and take into account the discourse organisation, layout, images and cultural appropriateness of health messaging. The implications of applying the PEMAT criteria are not only that start texts will become more accessible and better able to facilitate understanding-based trust relations, but also that translators are well placed to participate in the transcreations that may be required in the various target languages.

Effects of Calorie Restriction on Preserving Male Fertility Particularly in a State of Obesity.

Highlight the importance of exploring nutritional interventions that could be applied as alternative or supplementary therapeutic strategies to enhance men's fertility. Lifestyle choices haveprompted extensive discussions regarding its implications and applications as a complementary therapy. The growing concern over the decline in sperm quality underscores the urgency of investigating these alternative interventions. Calorie restriction (CR) has emerged as a promising strategy to improve male fertility. The efficacy of CR depends on factors like age, ethnicity and genetics. Clinical studies, such as CALERIE,have shown an improvement in serum testosterone level and sexual drive in men with or without obesity. Additionally, CR has been shown to positively impact sperm count and motility; however, its effects on sperm morphology and DNA fragmentation remain less clear, and the literature has shown discrepancies, mainly due to the nature of technically dependent assessment tools. The review advocates a personalized approach to CR, considering individual health profiles to maximize its benefits. It underscores the need for routine, accessible diagnostic techniques in male reproductive health. Itsuggests that future research should focus on personalized dietary interventions to improve male fertility and overall well-being in individuals with or without obesity and unravel CR's immediate and lasting effects on semen parameters in men without obesity.

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region.

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy.

Objective.In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast DL-based predictive dose algorithms for low-dose rate (LDR) prostate brachytherapy and to evaluate their uncertainty and stability.Approach.Data from 200 prostate patients, treated with125I sources, was collected. The Monte Carlo (MC) ground truth dose volumes were calculated with TOPAS considering the interseed effects and an organ-based material assignment. Two 3D convolutional neural networks, UNet and ResUNet TSE, were trained using the patient geometry and the seed positions as the input data. The dataset was randomly split into training (150), validation (25) and test (25) sets. The aleatoric (associated with the input data) and epistemic (associated with the model) uncertainties of the DL models were assessed.Main results.For the full test set, with respect to the MC reference, the predicted prostateD90metric had mean differences of -0.64% and 0.08% for the UNet and ResUNet TSE models, respectively. In voxel-by-voxel comparisons, the average global dose difference ratio in the [-1%, 1%] range included 91.0% and 93.0% of voxels for the UNet and the ResUNet TSE, respectively. One forward pass or prediction took 4 ms for a 3D dose volume of 2.56 M voxels (128 × 160 × 128). The ResUNet TSE model closely encoded the well-known physics of the problem as seen in a set of uncertainty maps. The ResUNet TSE rectum D2cchad the largest uncertainty metric of 0.0042.Significance.The proposed DL models serve as rapid dose predictors that consider the patient anatomy and interseed attenuation effects. The derived uncertainty is interpretable, highlighting areas where DL models may struggle to provide accurate estimations. The uncertainty analysis offers a comprehensive evaluation tool for dose predictor model assessment.

HPB ultrasound guidance techniques - Targeting

Ultrasound is an indispensable tool for intraoperative assessment and treatment of hepatopancreatobiliary pathology. As minimally invasive approaches to HPB surgery continue to expand and the benefits of parenchymal-sparing liver surgery are increasingly appreciated, skillful targeting will play an even bigger role in HPB surgical practice. Techniques for intraoperative targeting of liver lesions for the purposes of biopsy and ablation, particularly in the laparoscopic setting, are the focus of this chapter.Current evidence supports the use of ablation for a variety of liver lesions including hepatocellular carcinoma and metastatic colorectal cancer, particularly for smaller lesions.Successful targeting requires optimization of patient position and port placement. When targeting multiple lesions, thoughtful treatment sequencing is critical to maintaining visualization and optimizing outcomes.

Patient-Derived Blood-Brain Barrier Model for Screening Copper Bis(thiosemicarbazone) Complexes as Potential Therapeutics in Alzheimer's Disease.

Alzheimer's disease (AD) is the most prevalent cause of dementia characterized by a progressive cognitive decline. Addressing neuroinflammation represents a promising therapeutic avenue to treat AD; however, the development of effective antineuroinflammatory compounds is often hindered by their limited blood-brain barrier (BBB) permeability. Consequently, there is an urgent need for accurate, preclinical AD patient-specific BBB models to facilitate the early identification of immunomodulatory drugs capable of efficiently crossing the human AD BBB. This study presents a unique approach to BBB drug permeability screening as it utilizes the familial AD patient-derived induced brain endothelial-like cell (iBEC)-based model, which exhibits increased disease relevance and serves as an improved BBB drug permeability assessment tool when compared to traditionally employed in vitro models. To demonstrate its utility as a small molecule drug candidate screening platform, we investigated the effects of diacetylbis(N(4)-methylthiosemicarbazonato)copper(II) (CuII(atsm)) and a library of metal bis(thiosemicarbazone) complexes─a class of compounds exhibiting antineuroinflammatory therapeutic potential in neurodegenerative disorders. By evaluating the toxicity, cellular accumulation, and permeability of those compounds in the AD patient-derived iBEC, we have identified 3,4-hexanedione bis(N(4)-methylthiosemicarbazonato)copper(II) (CuII(dtsm)) as a candidate with good transport across the AD BBB. Furthermore, we have developed a multiplex approach where AD patient-derived iBEC were combined with immune modulators TNFα and IFNγ to establish an in vitro model representing the characteristic neuroinflammatory phenotype at the patient's BBB. Here, we observed that treatment with CuII(dtsm) not only reduced the expression of proinflammatory cytokine genes but also reversed the detrimental effects of TNFα and IFNγ on the integrity and function of the AD iBEC monolayer. This suggests a novel pathway through which copper bis(thiosemicarbazone) complexes may exert neurotherapeutic effects on AD by mitigating BBB neuroinflammation and related BBB integrity impairment. Together, the presented model provides an effective and easily scalable in vitro BBB platform for screening AD drug candidates. Its improved translational potential makes it a valuable tool for advancing the development of metal-based compounds aimed at modulating neuroinflammation in AD.

Hydrogen Safety Challenges: A Comprehensive Review on Production, Storage, Transport, Utilization, and CFD-Based Consequence and Risk Assessment

This review examines the central role of hydrogen, particularly green hydrogen from renewable sources, in the global search for energy solutions that are sustainable and safe by design. Using the hydrogen square, safety measures across the hydrogen value chain—production, storage, transport, and utilisation—are discussed, thereby highlighting the need for a balanced approach to ensure a sustainable and efficient hydrogen economy. The review also underlines the challenges in safety assessments, points to past incidents, and argues for a comprehensive risk assessment that uses empirical modelling, simulation-based computational fluid dynamics (CFDs) for hydrogen dispersion, and quantitative risk assessments. It also highlights the activities carried out by our research group SaRAH (Safety, Risk Analysis, and Hydrogen) relative to a more rigorous risk assessment of hydrogen-related systems through the use of a combined approach of CFD simulations and the appropriate risk assessment tools. Our research activities are currently focused on underground hydrogen storage and hydrogen transport as hythane.

Bedside preoperative predictors of difficult laryngeal exposure in microlaryngeal surgery.

Successful microlaryngeal surgery relies on an adequate laryngeal exposure. Recognizing the likelihood of challenging exposure prior to microlaryngeal surgery may assist in selecting the appropriate surgical approach and even prompt consideration of alternative treatment options. We aim to apply the mini-Laryngoscore, a preoperative assessment tool, to our study population and incorporate novel variables to optimize the prediction model. This single-center prospective cohort study included 80 consecutive patients undergoing elective microlaryngeal surgery, from January 1, to June 30, 2023. Each patient underwent a presurgical evaluation of 15 parameters and an intraoperative scoring of the anterior commissure visualization. These parameters were assessed for their association with difficult laryngeal exposure, using multiple logistic regression analysis. We created a novel prediction model for DLE and compared it with the existing model, the mini-Laryngoscore. Out of 80 patients, 24 (30%) patients had difficult laryngeal exposure, including 3 cases (3.8%) in which visualization of the anterior commissure was not possible. A large neck diameter (OR, 1.4; CI 1.1-1.9) and the presence of upper teeth (OR, 8.9; CI 1.3-62.8) were independent risk factors for a difficult laryngeal exposure, while a larger interincisors gap was the only independent protector factor (OR, 0.3; CI 0.1-0.8). The logistic regression model combining these three independent risk factors displayed a high discriminative value AUC = 0.89 (CI 0.81-0.97). The predictive performance of the mini-Laryngoscore was 0.73 (CI 0.62-0.85). Combining two parameters from the mini-Laryngoscore (upper jaw dental state and interincisors gap distance) with neck circumference measurement can accurately predict the risk of difficult laryngeal exposure.

I'm Great! I'm no good….: A case illustration of drama therapeutic work with a male offender of domestic violence in a forensic outpatient setting.

Treating perpetrators of aggressive behavior, like verbal aggression, intimidation, and bullying behavior resulting in aggressive incidents with others, is difficult. This group is often diagnosed with personality disorders and when legal measures applied, they are more often treated in a forensic setting for their problems. This article presents the case of a 54-year-old man, diagnosed with Borderline personality disorder, narcissistic and antisocial traits, mild depressive symptoms, and loss and grief, who has voluntarily had treatment in a forensic outpatient center to reduce aggression and change destructive patterns in relationships. Hating, judging, and self-defeating were the main reasons why the patient found himself ending up in the same situation repeatedly. The client received individual drama therapy sessions. The drama therapeutic approach included schema therapeutic elements, such as schema mode work with cards, as well as roleplay, imagery (with rescripting), improvisation, and psycho drama elements. As a result of drama therapy, the client reported less (active) aggression, less aggression in his relationships (partners/children/friends), but also an increased level of loneliness, and mild depressive symptoms. The client was more in touch with his vulnerability and was able to behave in a more adequate healthy way in relationships. Although self-esteem was still building up, there was a decrease of aggression and less conflict-seeking behavior as a result. Risk assessment tools (FARE-2& HONOS) and Schema therapy scales (YSQ and SMI) were used pre- and posttreatment confirming the improvements. This case promotes the use of dramatherapy in forensic outpatient care to be valuable in lowering risk recidivism and changing deeply rooted behavioral patterns.

Redefining Wound Healing Using Near-Infrared Spectroscopy.

No standard definition for a completely healed wound currently exists; it is recommended that providers use a reliable wound assessment tool to determine healing. The objective of this feasibility study was to determine if a point-of-care, noncontact, near-infrared (NIR) imaging device could provide an objective measure of wound resolution and guide clinical decision-making for the optimal time to transition from protective wound dressings and gradual return to full activity. In this single-center feasibility study, adult patients 18 years and older with a lower extremity wound of any size and etiology were seen weekly for wound assessment and standard-of-care treatment. The researchers performed serial imaging with a point-of-care, noncontact, NIR imaging device (Snapshot NIR ; Kent Imaging Inc) to assess the wound and surrounding skin and evaluated the difference in time to 100% reepithelialization on visual inspection and homogeneous tissue oxygen saturation levels at the wound site and surrounding closed skin envelope. An average time difference of 13.5 ± 10 days (median, 12 days; range, 0-35 days) was observed between 100% reepithelialization on visual wound inspection and imaging assessment. Further, NIR imaging could determine when a patient was at risk for recurrent wound breakdown. The addition of point-of-care, noncontact, NIR imaging may help guide clinical decision-making for the optimal time to transition from protective wound dressings with gradual return to full activity and minimize wound recurrence.

Antidepressant Prescribing Practices of Pediatric Palliative Care Providers.

Background: Mental health diagnoses can co-occur with complex medical illness in pediatric patients. Pediatricians may not feel comfortable with managing psychopharmacology for patients and access to child psychiatrists can be limited. Palliative care (PC) providers follow patients with serious illness longitudinally to address burdensome symptoms that affect quality of life and may be responsible for evaluation and treatment of mental health concerns; however, education in managing psychologic distress for pediatric palliative care (PPC) providers is limited. Objective: This study seeks to describe the antidepressant prescribing practices of PPC providers and describe their level of training and comfort in assessing for anxiety and depression and prescribing psychotropic medications. Methods: An electronic survey approved by the American Academy of Hospice and Palliative Medicine was distributed nationally to PPC providers. Results: A total of 58 providers responded to the survey (response rate 12.3%). Most reported prescribing a variety of antidepressants (79%). Very few used formal assessment tools to screen for depression (7%) or anxiety (16%). Less than a third of providers consulted child psychiatry before prescribing antidepressants (29%). More than half of providers (54.5%) had no formal training in assessment and treatment of anxiety and depression in pediatric patients. Despite this, many providers (70%) reported feeling comfortable in prescribing antidepressants while also endorsing interest in more training for behavioral health evaluation and treatment (82.5%). Conclusions: Limited training in assessing mental health concerns, prescribing, and managing psychopharmacology suggests an opportunity for more targeted education for pediatric PC providers regarding antidepressant prescribing practices.

Decision‐making analysis in post‐fire and explosion aftermath assessment tool: A fuzzy cognitive mapping approach

AbstractThis assessment tool was created to generate a decision‐making support system and assessment approach for a post‐fire (aftermath) and blast explosion impact. It uses a multidecision analysis neural network. Multidecision analysis is very crucial as the judgment of the assessment relies not only on engineering input but also on many contributing factors, such as lead time for replacement. This article outlines the framework for post‐incident explosion and fire‐damaged assessment using evaluation acceptance criteria and judgment that streamlines the process. Grounded theory (GT) and fuzzy cognitive mapping (FCM) techniques are presented and evaluated. Overall, this study aims to develop how the project organizations can ensure safety and asset integrity decision‐making by identifying hindrances and later developing a multicriteria analysis framework for the post‐incident assessment phase of implementation.

Financial Health Literacy and Community-Dwelling Older Adults: A Concept Analysis

Aim. To examine and clarify the concept financial health literacy (FHL) within the context of aging and healthcare. Background. Older adults have a high chronic disease burden and low financial and health literacy levels which often leads to high healthcare costs and poor self-management. Clarification of the concept FHL is necessary to better support nursing care and successful self-management. Design. Concept analysis using literary synthesis. Data Sources. Electronic databases were used to find scientific literature (i.e., PubMed, CINAHL, and Business Source Complete), and online dictionaries were used to find basic definitions. Review Methods. Walker and Avant’s eight-step method was used as a guide to construct a concept analysis of FHL. Clinical, aging, financial, and economic studies were reviewed to determine defining attributes, antecedents, and consequences of FHL on the older adult’s health. Results. FHL is defined as the knowledge, skills, and ability to make decisions that allow an individual to manage finances to optimally meet healthcare-related and household expenses, including resources to self-manage health, and plan for short-term, long-term, and end-of-life healthcare. Personal context, opportunity, and access are antecedents to FHL. There are 3 defining attributes: knowledge about health and financial-related concepts, skills in health and financial planning, and healthcare and financial-related decision-making behaviors. The 4 consequences of FHL include effective healthcare utilization, effective cost management, effective self-management, and positive health outcomes. Conclusions. FHL is a complex, multidimensional concept. A better understanding of this concept has significant nursing implications for research, clinical, practice, education, and policy development. Older adults have unique health and financial needs due to the complexity of retirement, living on a fixed income, and self-management of chronic diseases. Development of a FHL assessment tool and intervention is needed and may be supported based on the results of this concept analysis.

Suitability of risk assessment tools used during the portfolio recommendation process

Orientation: Investors are overwhelmed with Collective Investment Schemes (CIS) portfolio options.Research purpose: The study set out to assess the emerging themes considered essential and prevalent in establishing a risk profile, establishing a framework for risk assessment tools, and evaluating existing risk assessment tools used in the industry.Motivation for the study: In 2020, newly amended legislation confirmed the importance of a risk assessment. This legislation made it mandatory and compulsory for financial planners to conduct a risk profile analysis concerning investment products in South Africa. Consequently, CIS have implemented various risk assessment tools to establish the investor risk profile.Research approach/design and method: Documentary research methodology was employed, where secondary data were analysed qualitatively. Twelve risk assessment tools were collected, and the established framework was used to evaluate existing risk assessment tools.Main findings: A sound theoretical framework for risk assessment tools, which is comprehensive in nature and include demographic factors, risk categorisation, and regulatory factors, was established. The results indicate that current tools used in the industry are inconsistent and do not address all the factors required to establish an investor risk profile.Practical/managerial implications: The study is significant in that it guides the financial services industry into the elements of assessment in establishing an investor risk profile.Contribution/value-add: A risk profile analysis is compulsory for financial planning. Financial planners and policymakers can consider the established framework to implement a standardised, comprehensive, holistic, risk assessment tool.

Prognostic risk models for incident hypertension: A PRISMA systematic review and meta-analysis.

Our goal was to review the available literature on prognostic risk prediction for incident hypertension, synthesize performance, and provide suggestions for future work on the topic. A systematic search on PUBMED and Web of Science databases was conducted for studies on prognostic risk prediction models for incident hypertension in generally healthy individuals. Study-quality was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST) checklist. Three-level meta-analyses were used to obtain pooled AUC/C-statistic estimates. Heterogeneity was explored using study and cohort characteristics in meta-regressions. From 5090 hits, we found 53 eligible studies, and included 47 in meta-analyses. Only four studies were assessed to have results with low risk of bias. Few models had been externally validated, with only the Framingham risk model validated more than thrice. The pooled AUC/C-statistics were 0.82 (0.77-0.86) for machine learning models and 0.78 (0.76-0.80) for traditional models, with high heterogeneity in both groups (I2 > 99%). Intra-class correlations within studies were 60% and 90%, respectively. Follow-up time (P = 0.0405) was significant for ML models and age (P = 0.0271) for traditional models in explaining heterogeneity. Validations of the Framingham risk model had high heterogeneity (I2 > 99%). Overall, the quality of included studies was assessed as poor. AUC/C-statistic were mostly acceptable or good, and higher for ML models than traditional models. High heterogeneity implies large variability in the performance of new risk models. Further, large heterogeneity in validations of the Framingham risk model indicate variability in model performance on new populations. To enable researchers to assess hypertension risk models, we encourage adherence to existing guidelines for reporting and developing risk models, specifically reporting appropriate performance measures. Further, we recommend a stronger focus on validation of models by considering reasonable baseline models and performing external validations of existing models. Hence, developed risk models must be made available for external researchers.

Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment.

Care for patients with heart failure (HF) causes a substantial load on health care systems where a prominent challenge is the elevated rate of readmissions within 30 days following initial discharge. Clinical professionals face high levels of uncertainty and subjectivity in the decision-making process on the optimal timing of discharge. Unwanted hospital stays generate costs and cause stress to patients and potentially have an impact on care outcomes. Recent studies have aimed to mitigate the uncertainty by developing and testing risk assessment tools and predictive models to identify patients at risk of readmission, often using novel methods such as machine learning (ML). This study aims to investigate how a developed clinical decision support (CDS) tool alters the decision-making processes of health care professionals in the specific context of discharging patients with HF, and if so, in which ways. Additionally, the aim is to capture the experiences of health care practitioners as they engage with the system's outputs to analyze usability aspects and obtain insights related to future implementation. A quasi-experimental design with randomized crossover assessment will be conducted with health care professionals on HF patients' scenarios in a region located in the South of Sweden. In total, 12 physicians and nurses will be randomized into control and test groups. The groups shall be provided with 20 scenarios of purposefully sampled patients. The clinicians will be asked to take decisions on the next action regarding a patient. The test group will be provided with the 10 scenarios containing patient data from electronic health records and an outcome from an ML-based CDS model on the risk level for readmission of the same patients. The control group will have 10 other scenarios without the CDS model output and containing only the patients' data from electronic medical records. The groups will switch roles for the next 10 scenarios. This study will collect data through interviews and observations. The key outcome measures are decision consistency, decision quality, work efficiency, perceived benefits of using the CDS model, reliability, validity, and confidence in the CDS model outcome, integrability in the routine workflow, ease of use, and intention to use. This study will be carried out in collaboration with Cambio Healthcare Systems. The project is part of the Center for Applied Intelligent Systems Research Health research profile, funded by the Knowledge Foundation (2021-2028). Ethical approval for this study was granted by the Swedish ethical review authority (2022-07287-02). The recruitment process of the clinicians and the patient scenario selection will start in September 2023 and last till March 2024. This study protocol will contribute to the development of future formative evaluation studies to test ML models with clinical professionals. PRR1-10.2196/52744.

Analysis of the quality information provided by “Dr. YouTube™” on premature ejaculation

ABSTRACT Background: YouTube™ is an important online resource to access health-related online information by the public worldwide. However, the quality of information available on it has not been adequately characterized. Aim: To assess the quality and reliability of information available on the treatment of premature ejaculation (PME) on YouTube™ in the Hindi and English language videos. Materials and Methods: A total of 151 (Hindi: 109, English: 42) YouTube videos were selected for assessment. The quality was evaluated using structured tools: Patient Education Materials Assessment Tool (PEMAT); and a 5-point modified DISCERN questionnaire (Range: 1-serious shortcomings; 5-minimal shortcomings). PEMAT assesses the understandability and actionability of video as separate percentages. Results: Three most common treatments suggested for PME were Kegel exercise (22.5%), start–stop technique (21.9%), and antidepressant medications (20.5%). Antidepressant medications, stop-squeeze techniques, and psychotherapy were more frequently suggested in English videos, whereas ayurvedic or herbal medicines were more frequently suggested in Hindi videos. About two-thirds of videos presented information in an easy-to-understand and actionable manner (PEMAT scores ≥70%). Only 6% of videos had a DISCERN score of ≥4, indicating good overall quality of information presented in them. Conclusion: People likely to encounter poor-quality information when seeking information for PME treatment on YouTube. A large number of videos suggested ineffective or unproven treatment strategies for PME. Healthcare professionals need to be mindful of this while counselling patients, and guide them regarding useful and reliable sources of health information available online.

Demonstration Exam in the Modern System of Assessment Funds at the Pedagogical University

Introduction. The problem of the study involves the need to find effective procedures for assessing the competence and level of readiness for professional activities of future specialists, their readiness to work in conditions of uncertainty. The aim of the study is to identify the possibilities of using the demonstration exam to improve the quality of implementation of educational programs of higher education and to ensure the effectiveness of the assessment procedure. Methods: analysis and synthesis of analytical data, dissertation researches, regulatory and legislative framework. Outcomes. It is revealed that one of the options for improving the assessment procedure in the structure of final certification in pedagogical education is a demonstration exam. The content of the tasks, regardless of the training profile of future teachers, is based on the provisions of professional standards, which determines their form – situational tasks, problem tasks or cases. Tasks can be based on the main subject type of activity, or include a general pedagogical situation and be included in the fund of assessment tools. The created funds of assessment tools, provided for by the requirements of exemplary educational programs, are a system for assessing the level of competence formation. Conclusion. The practice-oriented, objective and visual nature of the demo exam makes it possible to identify the level of formed competencies and assess possible gaps for further refinement of the graduateʼs professional qualities in the educational process. The authorʼs innovation consists in the use of a demonstration exam for internal independent assessment of the quality of education, external assessment of determining the level of training of teachers by the university, final and intermediate assessments.

Rationing of nursing care and assessment of work safety and a healthy work environment in intensive care units: A cross-sectional, correlational study

IntroductionRationing of nursing care, whichrefers to the aspects of care not delivered by nurses in an intensive care unit (ICU), has implicationsfor patient outcomes and experiences. ObjectivesThis study aimed to identify the extent to which nursing care is rationed in intensive care units, as well as asses quality of nursing care, and the level of job satisfaction and its correlation with an assessment of the climate of work safety, teamwork, and a healthy work environment. MethodologyA cross-sectional, correlational study was conducted. The study included 226 ICU nurses. It was conducted with the use of three instruments: the Perceived Implicit Rationing of Nursing Care (PRINCA) questionnaire on the rationing of nursing care, assessment of patient care quality and job satisfaction, American Association of Critical-Care Nurses Healthy Work Environment Assessment Tool (HWEAT) and the Safe Attitudes and Behaviours Questionnaire questionnaire in the version: Teamwork and Safety Climate (BePoZa). SettingsIntensive Care Units in Warmia and Mazury Region in Poland. Main Outcome MeasuresLevel of Nursing Care Rationing in Intensive Care Units. ResultsThe majority of participants were women (89.82 %) with a mean age of 42.47 years. The average score for nursing care rationing across all groups was 0.58. The mean score for the HWEAT was 2.7 and BePoZa was 3.72. The scores from the questionnaires were negatively correlated with the nursing care rationing scores, being −0.36 for the HWEAT and −0.45 for BePoZa. All correlation coefficients were statistically significant at a p-value of less than 0.05. ConclusionsIt is important to monitor work safety, teamwork climate, and standards of a healthy work environment in ICUs to minimise the risk of rationing nursing care. Implications for Clinical PracticeInterventions that enhance work organisation and teamwork can elevate nursing quality and job satisfaction in ICUs, while underestimating patient care tasks; thus, highlighting the need for further research on the factors influencing nursing performance.

Multivariable prediction models for fetal macrosomia and large for gestational age: A systematic review.

The identification of large for gestational age (LGA) and macrosomic fetuses is essential for counselling and managing these pregnancies. To systematically review the literature for multivariable prediction models for LGA and macrosomia, assessing the performance, quality and applicability of the included model in clinical practice. MEDLINE, EMBASE and Cochrane Library were searched until June 2022. We included observational and experimental studies reporting the development and/or validation of any multivariable prediction model for fetal macrosomia and/or LGA. We excluded studies that used a single variable or did not evaluate model performance. Data were extracted using the Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist. The model performance measures discrimination, calibration and validation were extracted. The quality and completion of reporting within each study was assessed by its adherence to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklist. The risk of bias and applicability were measured using PROBAST (Prediction model Risk Of Bias Assessment Tool). A total of 8442 citations were identified, with 58 included in the analysis: 32/58 (55.2%) developed, 21/58 (36.2%) developed and internally validated and 2/58 (3.4%) developed and externally validated a model. Only three studies externally validated pre-existing models. Macrosomia and LGA were differentially defined by many studies. In total, 111 multivariable prediction models were developed using 112 different variables. Model discrimination was wide ranging area under the receiver operating characteristics curve (AUROC 0.56-0.96) and few studies reported calibration (11/58, 19.0%). Only 5/58 (8.6%) studies had a low risk of bias. There are currently no multivariable prediction models for macrosomia/LGA that are ready for clinical implementation.