A field study of data analysis exercises in a bachelor physics course using the internet platform VISPA

Bachelor physics lectures on particle physics and astrophysics were complemented by exercises related to data analysis and data interpretation at the RWTH Aachen University recently. The students performed these exercises using the internet platform VISPA, which provides a development environment for physics data analyses. We describe the platform and its application within the physics course, and present the results of a student survey. The students acceptance of the learning project was positive. The level of acceptance was related to their individual preference for learning with a computer. Furthermore, students with good programming skills favor working individually, while students who attribute themselves having low programming abilities favor working in teams. The students appreciated approaching actual research through the data analysis tasks.Comment: 21 pages, 8 figures, 1 table, for the internet platform VISPA see http://vispa.physik.rwth-aachen.d

Primary care practitioners’ diagnostic action when the patient may have cancer : an exploratory vignette study in 20 European countries

Availability of data To avoid the risk of identification of individual participants, the datasets generated and analysed during the current study are not publicly available. However, they are available (with any possible identifying information redacted) from the corresponding author on reasonable request. Funding This study received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. ALN’s time is supported by the National Institute for Health Research (NIHR) Imperial Patient Safety Translation Research Centre, with her infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). Acknowledgements We would like to thank all the PCPs who piloted the questionnaire and those who completed the survey. We would also like to thank the European GP Research Network for its support. We are grateful to Prof. Barbara Silverman and Prof. Lital Keinan for the data on cancer survival rates in Israel, and to Dr Yochai Schonmann for his work on those data. Two of the vignettes were used by kind permission of the ICBP; we also thank Dr Peter Murchie and Dr Rhona Auckland, who generously provided the other two vignettes. Prof. Antonius Schneider kindly organised the Technical University of Munich’s data collection.Peer reviewedPublisher PD

Identifying important health system factors that influence primary care practitioners' referrals for cancer suspicion : a European cross-sectional survey

ALN is supported by the National Institute for Health Research (NIHR) Imperial Patient Safety Translation Research Centre, with infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). Prepublication history and additional material for this paper are available online. To view these files, please visit the journal online (http://dx.doi.org/10.1136/bmjopen-2018-022904).Peer reviewedPublisher PD

Why do European primary care physicians sometimes not think of, or act on, a possible cancer diagnosis? : A qualitative study

Funding The Swedish application for ethical approval was funded by the Jämtland Cancer and Nursing Foundation. The study had no other external fundingPeer reviewedPostprin

General practitioners' deprescribing decisions in older adults with polypharmacy: a case vignette study in 31 countries.

BACKGROUND General practitioners (GPs) should regularly review patients' medications and, if necessary, deprescribe, as inappropriate polypharmacy may harm patients' health. However, deprescribing can be challenging for physicians. This study investigates GPs' deprescribing decisions in 31 countries. METHODS In this case vignette study, GPs were invited to participate in an online survey containing three clinical cases of oldest-old multimorbid patients with potentially inappropriate polypharmacy. Patients differed in terms of dependency in activities of daily living (ADL) and were presented with and without history of cardiovascular disease (CVD). For each case, we asked GPs if they would deprescribe in their usual practice. We calculated proportions of GPs who reported they would deprescribe and performed a multilevel logistic regression to examine the association between history of CVD and level of dependency on GPs' deprescribing decisions. RESULTS Of 3,175 invited GPs, 54% responded (N = 1,706). The mean age was 50 years and 60% of respondents were female. Despite differences across GP characteristics, such as age (with older GPs being more likely to take deprescribing decisions), and across countries, overall more than 80% of GPs reported they would deprescribe the dosage of at least one medication in oldest-old patients (> 80 years) with polypharmacy irrespective of history of CVD. The odds of deprescribing was higher in patients with a higher level of dependency in ADL (OR =1.5, 95%CI 1.25 to 1.80) and absence of CVD (OR =3.04, 95%CI 2.58 to 3.57). INTERPRETATION The majority of GPs in this study were willing to deprescribe one or more medications in oldest-old multimorbid patients with polypharmacy. Willingness was higher in patients with increased dependency in ADL and lower in patients with CVD

Prediction of Chronic Stress and Protective Factors in Adults: Development of an Interpretable Prediction Model Based on XGBoost and SHAP Using National Cross-sectional DEGS1 Data

BackgroundChronic stress is highly prevalent in the German population. It has known adverse effects on mental health, such as burnout and depression. Known long-term effects of chronic stress are cardiovascular disease, diabetes, and cancer. ObjectiveThis study aims to derive an interpretable multiclass machine learning model for predicting chronic stress levels and factors protecting against chronic stress based on representative nationwide data from the German Health Interview and Examination Survey for Adults, which is part of the national health monitoring program. MethodsA data set from the German Health Interview and Examination Survey for Adults study including demographic, clinical, and laboratory data from 5801 participants was analyzed. A multiclass eXtreme Gradient Boosting (XGBoost) model was constructed to classify participants into 3 categories including low, middle, and high chronic stress levels. The model’s performance was evaluated using the area under the receiver operating characteristic curve, precision, recall, specificity, and the F1-score. Additionally, SHapley Additive exPlanations was used to interpret the prediction XGBoost model and to identify factors protecting against chronic stress. ResultsThe multiclass XGBoost model exhibited the macroaverage scores, with an area under the receiver operating characteristic curve of 81%, precision of 63%, recall of 52%, specificity of 78%, and F1-score of 54%. The most important features for low-level chronic stress were male gender, very good general health, high satisfaction with living space, and strong social support. ConclusionsThis study presents a multiclass interpretable prediction model for chronic stress in adults in Germany. The explainable artificial intelligence technique SHapley Additive exPlanations identified relevant protective factors for chronic stress, which need to be considered when developing interventions to reduce chronic stress