Different Levels Of Expertise Research Articles

#1357 Regional and national hospitalization burden of lupus nephritis and systemic lupus erythematous in Spain

Abstract Background and Aims The regional epidemiology of Systemic lupus erythematosus (SLE) and lupus nephritis (LN) within the same country is poorly understood. Being a rare disease, its severity may be influenced by local expertise and treatment protocols, especially when healthcare systems are fragmented, like in Spain (17 different healthcare systems in 17 Autonomous Community (AACC), population range 319.796 to 8.472.407), resulting in potentially different levels of expertise in regional referral centers. Additional heterogeneity may derive from different specialists (rheumatology, internal medicine, nephrology) caring for SLE and LN. We aim to investigate the disease burden of SLE and LN in Spain and its AACC between 2019 and 2021, and to characterize factors that may influence this burden. Method The primary diagnostic data and average cost of SLE and NL hospitalization were extracted from the Minimum Basic Data Set (MBDS, Ministry of Health) that contains data from private and public hospitals. Sociodemographic data were obtained from the National Statistics Institute. Results From 2019 to 2021, there were 872 LN and 3612 SLE nationwide hospitalizations. Over 60% occurred in Andalucia, Catalonia, and Madrid, which account for 48% of Spanish population. Nationwide, the incidence of LN and SLE hospitalization was 1.44 and 4.59 per 100 000, respectively. However, regional variability was large, with a 3.7-fold difference for LN and a 7.3-fold difference for SLE between Madrid and Valencia, 2 of the more populated AACC. The median LN/SLE hospitalization ratio was 0.33. Relative risk for hospitalization, compared to the national mean, ranged in AACC from 0.37 (Baleares) to 2.55 (La Rioja) for LN and from 0.22 (Baleares) to 3.67 (Ceuta and Melilla) for SLE (Fig. 1A). Heterogeneity was larger at the provincial level where 10/50 provinces had significantly higher or lower relative risk than the national mean (Fig. 1B). The length of SLE/LN hospitalizations was very variable across specialties and AACC. There was a trend for shorter duration in Nephrology and longer in Internal Medicine for both LN and SLE. Nephrology was mainly responsible (76%) for LN hospitalization, with regional differences. For SLE hospitalization, Nephrology was also most commonly in charge. Heterogeneity was larger at the province level within the same AACC. The average All-Patient-Related (APR) cost per LN and SLE hospitalization episodes was €5254 and €4376, respectively, with significant geographical variability. Total annual hospitalization costs varied significantly among AACC, ranging from €8683 (Ceuta and Melilla) to €682512 (Catalonia) for LN and from €68361 (Ceuta and Melilla) to €2229456 (Madrid) for SLE. Adjusted per million population, total LN hospitalization cost ranged from €27920 (Baleares) to €179248 (La Rioja), and SLE cost from €91563 (Baleares) to €399693 (Ceuta and Melilla). When adjusted by €1000 of average household net income, the budget burden of LN hospitalization was highest in La Rioja (€5812 per €1000 of average household net income) and lowest in Baleares (€809 per €1000), while for SLE was highest in Murcia (€11186 per €1000) and lowest in Baleares (€2652 per €1000) (Fig. 2A,B). Conclusion In conclusion, the burden of LN and SLE hospitalization is heterogeneous across and within Spanish AACC, with large regional differences in the distribution of cases, costs and specialists who care for these patients. The analysis of these differences may contribute to benchmarking of best practices, decreasing clinical practice heterogeneity, optimizing care for SLE and LN and improving outcomes.

Report from a Tibetan Monastery: EEG neural correlates of concentrative and analytical meditation.

The positive effects of meditation on human wellbeing are indisputable, ranging from emotion regulation improvement to stress reduction and present-moment awareness enhancement. Changes in brain activity regulate and support these phenomena. However, the heterogeneity of meditation practices and their cultural background, as well as their poor categorization limit the generalization of results to all types of meditation. Here, we took advantage of a collaboration with the very singular and precious community of the Monks and Geshes of the Tibetan University of Sera-Jey in India to study the neural correlates of the two main types of meditation recognized in Tibetan Buddhism, namely concentrative and analytical meditation. Twenty-three meditators with different levels of expertise underwent to an ecological (i.e., within the monastery) EEG acquisition consisting of an analytical and/or concentrative meditation session at "their best," and with the only constraint of performing a 5-min-long baseline at the beginning of the session. Time-varying power-spectral-density estimates of each session were compared against the baseline (i.e., within session) and between conditions (i.e., analytical vs. concentrative). Our results showed that concentrative meditation elicited more numerous and marked changes in the EEG power compared to analytical meditation, and mainly in the form of an increase in the theta, alpha and beta frequency ranges. Moreover, the full immersion in the Monastery life allowed to share the results and discuss their interpretation with the best scholars of the Monastic University, ensuring the identification of the most expert meditators, as well as to highlight better the differences between the different types of meditation practiced by each of them.

Computer-aided diagnosis system for optical diagnosis of colorectal polyps under white light imaging

ObjectivesThis study presents a novel computer-aided diagnosis (CADx) designed for optically diagnosing colorectal polyps using white light imaging (WLI).We aimed to evaluate the effectiveness of the CADx and its auxiliary role among endoscopists with different levels of expertise. MethodsWe collected 2,324 neoplastic and 3,735 nonneoplastic polyp WLI images for model training, and 838 colorectal polyp images from 740 patients for model validation. We compared the diagnostic accuracy of the CADx with that of 15 endoscopists under WLI and narrow band imaging (NBI). The auxiliary benefits of CADx for endoscopists of different experience levels and for identifying different types of colorectal polyps was also evaluated. ResultsThe CADx demonstrated an optical diagnostic accuracy of 84.49%, showing considerable superiority over all endoscopists, irrespective of whether WLI or NBI was used (P < 0.001). Assistance from the CADx significantly improved the diagnostic accuracy of the endoscopists from 68.84% to 77.49% (P = 0.001), with the most significant impact observed among novice endoscopists. Notably, novices using CADx-assisted WLI outperform junior and expert endoscopists without such assistance. ConclusionsThe CADx demonstrated a crucial role in substantially enhancing the precision of optical diagnosis for colorectal polyps under WLI and showed the greatest auxiliary benefits for novice endoscopists.

Ambulatory pediatricians: how to bridge the gaps in diagnosis and care coordination for neurodevelopmental disorders in France.

The organization of healthcare pathways for neurodevelopmental disorders (NDD) relies on different levels of expertise depending on the complexity of these disorders. NDDs affect between 8% and 15% of children. Historically, national recommendations and healthcare planning measures were initially devoted to autism spectrum disorders and were gradually extended to Attention deficit hyperactivity disorder (ADHD) and specific learning and development disorders. Private doctors play an increasing role in these pathways at different levels of care due to difficulties in organization, particularly in the health and social sector. The aim of this work was to evaluate the contribution of second-line private doctors in the diagnosis and care of children affected by NDD. A first series of surveys in 2016 evaluated the level of commitment of primary care pediatricians; this online national survey was repeated in 2023 among 1,430 members of the French Association of Ambulatory Pediatrics (Association Française de Pédiatrie Ambulatoire: AFPA) to assess their training, current and future involvement, and activity in NDD care. Analysis was performed by the main author using Epi-Info software. The study identified in 2023 214 second-line private doctors (14% of all pediatricians in activity), of which 185 agreed to appear in a directory published the same year by the AFPA to facilitate referrals from other professionals. Sex ratio of responders is usual for paediatricians: 79.5%/20.5% (F/M), with a distribution among ages showing a slight increase of the age range between age 51-60 (30.5%). Our data indicate that in France in 2022, second-line private doctors made 48%-53% of NDD diagnoses, 24%-26.4% of follow-up consultations and declare to be accountable for 21% of initial prescriptions for Methylphenidate. Among these second-line doctors, 40% had completed a post-university degree on NDD, 74.3% had completed professional development training (PDT) and 85.2% had completed either or both types of training. Most doctors participating in the survey wanted to improve their level of practice, suggesting that in five years, the number of second-line private doctors will increase by 20% to 244 despite 24 planned retirements within the same period. This data probably underestimates the role of private doctors in NDD diagnosis, follow-up, and initial Methylphenidate prescriptions given the unfavourable working conditions (no financial compensation for long appointments, difficulty accessing paramedical and psychological assessments). Our data confirms that diagnosis and care coordination in the various presentations of NDD may rely on different types of practices and specializations: medical and social professionals, mental health professionals, but also a growing body of medical doctors involved in developmental and behavioural pediatrics. This data and reflection will be helpful for organizing healthcare in France or in other countries. Main study limitation relies in the self-declaration of MD's involvement in NDD and could not evaluate the activity of employed MD's from the social and medico social sector, nor be based on the national databases for prescription. It remains however the first attempt of characterization of medical activity at the national level in France for NDD.

Comparison of clinical geneticist and computer visual attention in assessing genetic conditions.

Artificial intelligence (AI) for facial diagnostics is increasingly used in the genetics clinic to evaluate patients with potential genetic conditions. Current approaches focus on one type of AI called Deep Learning (DL). While DL- based facial diagnostic platforms have a high accuracy rate for many conditions, less is understood about how this technology assesses and classifies (categorizes) images, and how this compares to humans. To compare human and computer attention, we performed eye-tracking analyses of geneticist clinicians (n = 22) and non-clinicians (n = 22) who viewed images of people with 10 different genetic conditions, as well as images of unaffected individuals. We calculated the Intersection-over-Union (IoU) and Kullback-Leibler divergence (KL) to compare the visual attentions of the two participant groups, and then the clinician group against the saliency maps of our deep learning classifier. We found that human visual attention differs greatly from DL model's saliency results. Averaging over all the test images, IoU and KL metric for the successful (accurate) clinician visual attentions versus the saliency maps were 0.15 and 11.15, respectively. Individuals also tend to have a specific pattern of image inspection, and clinicians demonstrate different visual attention patterns than non-clinicians (IoU and KL of clinicians versus non-clinicians were 0.47 and 2.73, respectively). This study shows that humans (at different levels of expertise) and a computer vision model examine images differently. Understanding these differences can improve the design and use of AI tools, and lead to more meaningful interactions between clinicians and AI technologies.

A New Procedure-Based Assessment of Operative Skills in Gastric Bypass Surgery, Evaluated by Video Fragment Rating

PurposeFeedback on technical and procedural skills is essential during the training of residents and fellows. The aim of this study was to assess the performance of a newly created instrument for the assessment of operative skills using laparoscopic Roux-en-Y gastric bypass (LRYGB) video fragments.Materials and MethodsA new procedure-based assessment (PBA) was created by combining LRYGB key steps with a 5-point independence scale. LRYGB performed by residents and surgeons with different levels of expertise were video recorded. Fragments of the pouch creation, gastro-jejunostomy and jejunojejunostomy, were review by 12 expert bariatric surgeons and the operative skills assessed with the PBA, Objective Structured Assessment of Technical Skill (OSATS), and the Bariatric OSATS (BOSATS). The PBA was compared to the OSATS and BOSATS. Mean scores for all items of the different assessments were summarized and compared using a T-test.ResultsThe scores of the procedural steps were combined and compared for all levels. The mean scores for beginner, intermediate, and expert level were 2.71, 3.70, and 3.90 for the PBA; for the OSATS 1.84, 2.86, and 3.44; and for the BOSATS 2.78, 3.56, and 4.19. Each of these assessments differentiated between the three skill levels (all p < 0.05).ConclusionThe PBA discriminates well between different levels of operative skills. Similar patterns were found for the OSATS and BOSATS, showing that the randomly selected video fragments are representative samples for assessing skill level. Future research will demonstrate whether these results can be extrapolated to clinical training, and which scores allow for procedure certification.Graphical

Metacognition in musical practices: two studies with beginner and expert Brazilian musicians.

Metacognition is essential in the musical learning process as it involves understanding the purpose of each task, its planning, execution and evaluation. Considering the relevance of metacognitive processes, our objective in this study was to investigate how expert and beginner musicians manifest and verbalize their metacognitive processes in the context of preparing repertoire for a performance. The method used was a multi-case study carried out in two different contexts: with the five members of a brass quintet made up of professional musicians and with three beginner university violin students. The results obtained indicated that even at different levels of expertise, metacognitive processes were present in the musical practices of participants in the two contexts investigated. It was found that in both cases time management is a component of the preparation process in metacognitive regulation, however, for the beginner violinists in our sample it was a significantly more complex task than for the professional brass players. Regarding the learning monitoring and evaluation processes, it was possible to verify that beginner instrumentalists as well as professional musicians used declarative, conditional and procedural knowledge to carry out and reflect on their musical practices. These results have implications for both the individual and collective study process and for teaching processes. It is also observed that reflective thinking must accompany the processes of individual and collective interpretative-musical practices, considering that the musical results desired by musicians are related to the quality of cognitive, behavioral, affective and motivational undertakings pertinent to control and regulation of metacognitive processes.

Deep Learning-Based Analysis of Aortic Morphology From Three-Dimensional MRI.

Quantification of aortic morphology plays an important role in the evaluation and follow-up assessment of patients with aortic diseases, but often requires labor-intensive and operator-dependent measurements. Automatic solutions would help enhance their quality and reproducibility. To design a deep learning (DL)-based automated approach for aortic landmarks and lumen detection derived from three-dimensional (3D) MRI. Retrospective. Three hundred ninety-one individuals (female: 47%, age = 51.9 ± 18.4) from three sites, including healthy subjects and patients (hypertension, aortic dilation, Turner syndrome), randomly divided into training/validation/test datasets (N = 236/77/78). Twenty-five subjects were randomly selected and analyzed by three operators with different levels of expertise. 1.5-T and 3-T, 3D spoiled gradient-recalled or steady-state free precession sequences. Reinforcement learning and a two-stage network trained using reference landmarks and segmentation from an existing semi-automatic software were used for aortic landmark detection and segmentation from sinotubular junction to coeliac trunk. Aortic segments were defined using the detected landmarks while the aortic centerline was extracted from the segmentation and morphological indices (length, aortic diameter, and volume) were computed for both the reference and the proposed segmentations. Segmentation: Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetrical surface distance (ASSD); landmark detection: Euclidian distance (ED); model robustness: Spearman correlation, Bland-Altman analysis, Kruskal-Wallis test for comparisons between reference and DL-derived aortic indices; inter-observer study: Williams index (WI). A WI 95% confidence interval (CI) lower bound >1 indicates that the method is within the inter-observer variability. A P-value <0.05 was considered statistically significant. DSC was 0.90 ± 0.05, HD was 12.11 ± 7.79 mm, and ASSD was 1.07 ± 0.63 mm. ED was 5.0 ± 6.1 mm. A good agreement was found between all DL-derived and reference aortic indices (r >0.95, mean bias <7%). Our segmentation and landmark detection performances were within the inter-observer variability except the sinotubular junction landmark (CI = 0.96;1.04). A DL-based aortic segmentation and anatomical landmark detection approach was developed and applied to 3D MRI data for achieve aortic morphology evaluation. 3 TECHNICAL EFFICACY: Stage 2.

Kiosk 8R-FB-07 - Quantitative Segmentation Analysis in CMR Across Different Levels of Expertise – FBom Beginners to Experts

Kiosk 8R-FB-07 - Quantitative Segmentation Analysis in CMR Across Different Levels of Expertise – FBom Beginners to Experts

The added value of partnerships in implementing the UN sustainable development goals

Partnerships have become a key tool in the implementation of the United Nations (UN) Sustainable Development Goals (SDGs). Partnerships can scale up the impact of initiatives by leveraging the strengths and reach of each involved partner. This allows for the replication and expansion of successful projects and programs. In the context of the UN SDGs, partnerships can play a key role in their effective implementation, due to their ability to bring together a variety of stakeholders from different sectors and with different levels of expertise and experience. By leveraging the skills, resources, and capacities of different stakeholders, partnerships can contribute to creating synergies that are essential for the successful implementation of the SDGs. Despite the role of partnerships and their potential value, there is a need for studies that can help understand their role and promote greater transparency and accountability in the implementation of the SDGs. Against this background, this article outlines the concept of partnerships and their values, followed by a description of the partnerships for sustainable development, concerning the implementation of the SDGs and its main features. Some examples of relevant partnerships are presented, outlining their scope and degree of success. Based on the experiences gathered specific suggestions on how to foster partnerships to foster the implementation of sustainable development are provided. It is crucial to define common objectives to ensure alignment and a strong foundation for collaboration, involving diverse stakeholders, including governments, businesses, non-governmental organizations (NGOs), academia, and local communities, thus bringing unique perspectives and resources. Open and transparent communication builds trust and encourages the sharing of ideas and challenges. Additionally, demonstrating the benefits for each partner, whether in reputation, market access, or cost reduction, motivates active engagement, establishes incentive structures, and allows to celebrate successes. Pooling resources, knowledge, and expertise enhances the effectiveness of sustainable development initiatives, encouraging long-term commitments and fostering adaptability in the face of complex challenges. These are specific strategies that highlight the relevance of these findings, in comparison to existing work. Partnerships have evolved into indispensable instruments for the realization of the UN SDGs. Their transformative potential is expected to grow as the future trend, driven by the ongoing need for collaborative solutions to global challenges, becoming instrumental in addressing pressing global issues such as climate change, public health crises, and economic inequalities. In the coming years, a surge in research and initiatives focusing on optimizing partnership models, governance structures, and monitoring mechanisms to enhance accountability and transparency, is anticipated. Furthermore, the integration of digital technologies and data-driven insights into partnership strategies may revolutionize their impact and efficiency. Overall, the evolution of partnerships as a vital force in global sustainability presents a promising future trend with broader applications and a crucial role in addressing multifaceted challenges beyond the SDGs, as demonstrated in this study.

Comparison of the Accuracy in Provisional Diagnosis of 22q11.2 Deletion and Williams Syndromes by Facial Photos in Thai Population Between De-Identified Facial Program and Clinicians.

There are more than 6000 genetic syndromes, therefore the recognition of facial patterns may present a challenge for clinicians. The 22q11.2 deletion syndrome (22q11.2 DS) and Williams syndrome (WS) are two different genetic syndromes but share some common phenotypic traits and subtle facial dysmorphisms. Therefore, any tool that would help clinicians recognize genetic syndromes would likely result in a more accurate diagnosis. The syndrome identification accuracy was compared between 2 different facial analysis algorithms (DeepGestalt and GestaltMatcher) of the Face2Gene (F2G) tool and a group of 9 clinicians with different levels of expertise before and after using F2G for a cohort of 64 Thai participants' frontal facial photos divided into 3 groups of 22q11.2 DS, WS and unaffected controls. The higher accuracy from the DeepGestalt algorithm than from clinicians was demonstrated, especially when comparing between the two syndromes. The accuracy was highest when clinicians use the tool combined with their own decision-making process. The tool's second algorithm, GestaltMatcher revealed clear separation among these three groups of photos. The result of F2G outperforming clinicians was not surprising. However, the highest increase in accuracy was with nondysmorphology clinicians using F2G. Face2Gene would be a useful tool to help clinicians in facial recognition of genetic syndromes, before ordering specific tests to confirm the definite diagnosis.

Marine Citizen Science and the Conservation of Mediterranean Corals: The Relevance of Training, Expert Validation, and Robust Sampling Protocols

Marine Citizen Science (MCS) has emerged as a promising tool to enhance conservation efforts. Although the quality of volunteer data has been questioned, the design of specific protocols, effective training programs, and data validation by experts have enabled us to overcome these quality concerns, thus ensuring data reliability. Here, we validated the effectiveness of volunteer training in assessing the conservation status of Mediterranean coral species. We conducted a comparative analysis of data collected by volunteers with different levels of expertise, demonstrating improvements in data precision and accuracy with only one training session, thereby achieving values equivalent to those obtained by scientists. These outcomes align with the feedback received from volunteers through a qualitative survey. Finally, we analysed the data generated by volunteers and validated by experts using the developed protocol in the Coral Alert project from the Observadores del Mar MCS initiative. Our findings highlight the importance of proper training, expert validation, robust sampling protocols, and a well-structured platform to ensure the success of long-term MCS projects. Overall, our results stress the key role MCS plays in enhancing the conservation and management strategies designed to mitigate the ongoing environmental crisis.

Using AI to Improve Radiologist Performance in Detection of Abnormalities on Chest Radiographs.

Background Chest radiography remains the most common radiologic examination, and interpretation of its results can be difficult. Purpose To explore the potential benefit of artificial intelligence (AI) assistance in the detection of thoracic abnormalities on chest radiographs by evaluating the performance of radiologists with different levels of expertise, with and without AI assistance. Materials and Methods Patients who underwent both chest radiography and thoracic CT within 72 hours between January 2010 and December 2020 in a French public hospital were screened retrospectively. Radiographs were randomly included until reaching 500 radiographs, with about 50% of radiographs having abnormal findings. A senior thoracic radiologist annotated the radiographs for five abnormalities (pneumothorax, pleural effusion, consolidation, mediastinal and hilar mass, lung nodule) based on the corresponding CT results (ground truth). A total of 12 readers (four thoracic radiologists, four general radiologists, four radiology residents) read half the radiographs without AI and half the radiographs with AI (ChestView; Gleamer). Changes in sensitivity and specificity were measured using paired t tests. Results The study included 500 patients (mean age, 54 years ± 19 [SD]; 261 female, 239 male), with 522 abnormalities visible on 241 radiographs. On average, for all readers, AI use resulted in an absolute increase in sensitivity of 26% (95% CI: 20, 32), 14% (95% CI: 11, 17), 12% (95% CI: 10, 14), 8.5% (95% CI: 6, 11), and 5.9% (95% CI: 4, 8) for pneumothorax, consolidation, nodule, pleural effusion, and mediastinal and hilar mass, respectively (P < .001). Specificity increased with AI assistance (3.9% [95% CI: 3.2, 4.6], 3.7% [95% CI: 3, 4.4], 2.9% [95% CI: 2.3, 3.5], and 2.1% [95% CI: 1.6, 2.6] for pleural effusion, mediastinal and hilar mass, consolidation, and nodule, respectively), except in the diagnosis of pneumothorax (-0.2%; 95% CI: -0.36, -0.04; P = .01). The mean reading time was 81 seconds without AI versus 56 seconds with AI (31% decrease, P < .001). Conclusion AI-assisted chest radiography interpretation resulted in absolute increases in sensitivity for all radiologists of various levels of expertise and reduced the reading times; specificity increased with AI, except in the diagnosis of pneumothorax. © RSNA, 2023 Supplemental material is available for this article.

Cinematographers’ Perceptual Professionalization from Novices to Experts: Observations from an Eye-tracking Case Study

Abstract Cinematographers represent a group of experts whose professional skills depend to a great extent on their visual perceptual abilities. By the term perceptual professionalization, we emphasize the embodied dynamics of perceptual learning processes that shape the ways in which cinematographers make creative decisions during their daily practices. Novice cinematographers are initiated in film schools and during assisting jobs to a range of technical skills required for working as heads of the camera department in film productions. However, honing one’s perceptual skills as a professional cinematographer is nothing less than a lifelong process. While scientific studies show evidence for behavioral and physiological differences between experts and novices in many different fields, so far no such studies exist between professional cinematographers and novices. As a starting point for studying how cinematographers’ perceptual learning evolves from the level of novice to that of experienced professional, we assumed that the different expertise levels of cinematographers can be observed in the way they view moving images. We then conducted an eye-tracking case study where we identified differences in the gaze patterns between film professionals with different levels of expertise in cinematography during viewing a film trailer. As the experiential heuristics of creative decision-making of professional cinematographers largely rely on the practical skills accumulated in film work, in order to gain access to such knowledge, we also report how involving a practicing cinematographer both in designing the study and in analyzing the results provided us new insights to the topic under scrutiny. Based on our findings, a new study protocol is proposed.

Proposals to Reform the EU Customs Union

On 17 May 2023 the European Commission published the most ambitious and comprehensive proposals to reform the EU Customs Union since the establishing of the Customs Union in 1968. The Commission’s proposals follow a series of studies and consultations and is intended as a response to tensions that have arisen in the customs world as a result of a huge increase in trade volumes, a rapidly rising number of EU standards to be checked at borders, the shifting geopolitical reality and various crises. This contribution provides an overview of and critical reflection on the highlights of the proposals, enabling readers with different levels of expertise in customs law to get familiar with what has been proposed by the European Commission and to pave the way for further, in-depth research on these proposals EU Customs Union, reform, European Commission, customs legislation, UCC, e-commerce, importer, sanctions, EU Customs Data Hub, Trust and Check traders

Fostering knowledge integration through individual competencies: the impacts of perspective taking, reflexivity, analogical reasoning and tolerance of ambiguity and uncertainty

The present study examines the influence of individual competencies on knowledge integration in inter- and transdisciplinary work. Perspective taking, reflexivity, analogical reasoning, and tolerance of ambiguity and uncertainty were investigated as core competencies for fostering knowledge integration. Additional hypotheses assumed that the positive effects are valid in the scientific and economic contexts and that individual competencies predict knowledge integration at different levels of expertise. To test the hypotheses, 421 participants, comprised of students (N = 165) and individuals working in science (N = 152) and economics (N = 104), answered questionnaires on knowledge integration and competencies of knowledge integration in an online survey. Further questions collected demographic data and inquired about experience and expertise in inter- and transdisciplinary work. The main result was that all postulated competencies positively related to knowledge integration. Analogical reasoning and perspective taking showed the strongest relationships with knowledge integration. Further results show that all competencies are positively related to knowledge integration in the student and expert sample, yet the interrelationships differ between the scientific and economic sample. This investigation into the competencies of knowledge integration contributes to the education of inter- and transdisciplinarians in academia and business practice.

Co-simulation at different levels of expertise with Maestro2

When different simulation units are coupled together there are different choices to take, in particular regarding the granularity of such a co-simulation. When prototyping systems, it is typically favourable to get an initial idea of how a collection of simulation units work together without spending too much time setting up the orchestration. However, the granularity of such a simulation may be far away from what is needed in relation to the purpose of the simulation. In order to enable more flexibility and control over the co-simulation it is necessary to be able to steer the orchestration in a more detailed manner. This paper presents an open source co-simulation orchestration engine based on the Functional Mockup Interface standard but with a Domain Specific Language (DSL) enabling detailed control between the individual simulation units. The same tool can thus be used right out of the box for low-granularity co-simulation, and for high-granularity simulation the DSL enable a significant flexibility.

Focus on Text Producers: Plain and Easy Language in the Swiss Multilingual Institutional Context

This paper was carried out as part of the MACSI project (Multilingual Accessible Communication in Swiss Institutions) and focuses on a case study carried out with the Federal Statistical Office (FSO). The broad aim of this cooperation with the FSO is to evaluate ways of implementing multilingual accessible expert-lay communication on statistics. Switzerland boasts a long-established tradition of clear writing at institutional level. Being a multilingual country, accessible communication is institutionally mandatory in all its official languages.&#x0D; While most of the research on accessible communication is text and recipient-based, in this study we focused primarily on drafters, who are specialized experts in different domains, as well as on translators, who have to face the challenges of interlinguistic transfer of both specialized and plain communication. This paper presents the results from a questionnaire on accessibility submitted to drafters and translators within the FSO. The answers show that drafters address several target groups with the same text and or they produce different texts for different target groups. Moreover, both drafters and translators have little knowledge and experience with plain and easy language, although most of them are interested in putting more effort into writing lay-friendly texts. Thus, there is a need for sensitising and training drafters and translators so that they are able to adapt content, level of technicality and language to the different levels of expertise when producing different multilingual accessible texts.

Release velocity improvement with a new metronome-guided chest compression protocol: preliminary results of the RITMICO study

Abstract Introduction Annually, emergency medical services treat over 350’000 out-of-hospital cardiac arrests in the U.S. and over 25’000 in Europe. Outcomes vary widely, according also to the quality of the CardioPulmonary Resuscitation (CPR) provided. Recently, it was demonstrated how, on top of the compression phase, chest release phase is also important to obtain an adequate heart and brain perfusion. However, no studies describe how to ameliorate this parameter during resuscitation. Purpose We investigated if a modified metronome-guided procedure might improve chest compression release velocity during CPR simulation on standard manikin, compared to the standard procedure. Methods We developed a double-click metronome for CPR: the first click corresponds to chest compression and the second to the end of chest release. Volunteers with different levels of expertise in CPR and with a valid BLS-D certification have been included in the study. Each subject performed two CPR manikin simulations following a 4-min protocol with the standard and the modified metronome (Figure 1), in a random order. An Automated External Defibrillator (AED) equipped with pads allowed continuous measurement of CPR quality during simulations. Three CPR parameters have been measured: compression depth, rate and release velocity. CPR simulation was guided only by the external metronome, all audio prompts from the AED were silenced. The two procedures have been compared, in terms of CPR quality, using Wilcoxon signed-ranks test. Impact of subject-specific factors on the difference in CPR quality has been evaluated using stepwise regression. Results 151 volunteers were included in the study, 23 of them have been excluded due to incomplete data recording. Comparison between the two procedures (Figure 2) showed a significant increase of median chest compression depth (p&amp;lt;&amp;lt;0.001) and release velocity (p&amp;lt;0.05) with the modified metronome. Percentage of compressions within the optimal range was significantly higher for compression depth (p&amp;lt;0.05) and significantly lower for compression rate (p&amp;lt;0.01) with the modified metronome. Chest compression release velocity difference was not statistically significant (p=0.20). No significant impact of sex, age and level of expertise was observed. Conclusions The double-click metronome significantly increased CPR quality in terms of both compression depth and release velocity. The decrease of compressions within the optimal rate range in the modified procedure could be due to lack of familiarity with the new rhythm and needs further evaluation. Our study represents the first trial trying to improve chest compression release velocity. Demonstrating the efficacy of this procedure could pave the way to clinical trials in real resuscitations to confirm the potential impact on the outcome of out-of-hospital cardiac arrest.Study protocolComparison between the two procedures

Conversational Agents in Health Care: Expert Interviews to Inform the Definition, Classification, and Conceptual Framework.

Conversational agents (CAs), or chatbots, are computer programs that simulate conversations with humans. The use of CAs in health care settings is recent and rapidly increasing, which often translates to poor reporting of the CA development and evaluation processes and unreliable research findings. We developed and published a conceptual framework, designing, developing, evaluating, and implementing a smartphone-delivered, rule-based conversational agent (DISCOVER), consisting of 3 iterative stages of CA design, development, and evaluation and implementation, complemented by 2 cross-cutting themes (user-centered design and data privacy and security). This study aims to perform in-depth, semistructured interviews with multidisciplinary experts in health care CAs to share their views on the definition and classification of health care CAs and evaluate and validate the DISCOVER conceptual framework. We conducted one-on-one semistructured interviews via Zoom (Zoom Video Communications) with 12 multidisciplinary CA experts using an interview guide based on our framework. The interviews were audio recorded, transcribed by the research team, and analyzed using thematic analysis. Following participants' input, we defined CAs as digital interfaces that use natural language to engage in a synchronous dialogue using ≥1 communication modality, such as text, voice, images, or video. CAs were classified by 13 categories: response generation method, input and output modalities, CA purpose, deployment platform, CA development modality, appearance, length of interaction, type of CA-user interaction, dialogue initiation, communication style, CA personality, human support, and type of health care intervention. Experts considered that the conceptual framework could be adapted for artificial intelligence-based CAs. However, despite recent advances in artificial intelligence, including large language models, the technology is not able to ensure safety and reliability in health care settings. Finally, aligned with participants' feedback, we present an updated iteration of the conceptual framework for health care conversational agents (CHAT) with key considerations for CA design, development, and evaluation and implementation, complemented by 3 cross-cutting themes: ethics, user involvement, and data privacy and security. We present an expanded, validated CHAT and aim at guiding researchers from a variety of backgrounds and with different levels of expertise in the design, development, and evaluation and implementation of rule-based CAs in health care settings.