Artikel proefschrift Jos Dobber verschenen in Frontiers in Psychiatry 24 maart 2020: Background: Trials studying Motivational Interviewing (MI) to improve medication adherence in patients with schizophrenia showed mixed results. Moreover, it is unknown which active MI-ingredients are associated with mechanisms of change in patients with schizophrenia. To enhance the effect of MI for patients with schizophrenia, we studied MI's active ingredients and its working mechanisms. Methods: First, based on MI literature, we developed a model of potential active ingredients and mechanisms of change of MI in patients with schizophrenia. We used this model in a qualitative multiple case study to analyze the application of the active ingredients and the occurrence of mechanisms of change. We studied the cases of fourteen patients with schizophrenia who participated in a study on the effect of MI on medication adherence. Second, we used the Generalized Sequential Querier (GSEQ 5.1) to perform a sequential analysis of the MI-conversations aiming to assess the transitional probabilities between therapist use of MI-techniques and subsequent patient reactions in terms of change talk and sustain talk. Results: We found the therapist factor “a trusting relationship and empathy” important to enable sufficient depth in the conversation to allow for the opportunity of triggering mechanisms of change. The most important conversational techniques we observed that shape the hypothesized active ingredients are reflections and questions addressing medication adherent behavior or intentions, which approximately 70% of the time was followed by “patient change talk”. Surprisingly, sequential MI-consistent therapist behavior like “affirmation” and “emphasizing control” was only about 6% of the time followed by patient change talk. If the active ingredients were embedded in more comprehensive MI-strategies they had more impact on the mechanisms of change. Conclusions: Mechanisms of change mostly occurred after an interaction of active ingredients contributed by both therapist and patient. Our model of active ingredients and mechanisms of change enabled us to see “MI at work” in the MI-sessions under study, and this model may help practitioners to shape their MI-strategies to a potentially more effective MI.
BACKGROUND:Reintroduction of a food after negative food challenge (FC) faces many obstacles. There are no studies available about this subject in adults.OBJECTIVE:To investigate the frequency, reasons and risk factors of reintroduction failure in adults.METHODS:In this prospective study, adult patients received standardized follow-up care after negative FCs including a reintroduction scheme and supportive telephone consultations. Data were collected by telephone interview (2 weeks after FC) and questionnaires (at baseline and 6 months after FC(s)): food habits questionnaire, State-Trait Anxiety Inventory, Food Allergy Quality of Life Questionnaire-Adult Form and Food Allergy Independent Measure. Frequency and reasons of reintroduction failure were analysed using descriptive statistics and risk factors with univariate analyses.RESULTS:Eighty patients were included with, in total, 113 negative FCs. Reintroduction failed on short-term (2 weeks after FC) in 20% (95% CI: 13%-28%). Common reasons were symptoms upon ingestion during the reintroduction scheme (50%) and no need to eat the food (23%). On the long-term (5-12 months after FC(s)), reintroduction failure increased to 40% (95% CI: 28%-53%). Common reasons were atypical symptoms after eating the food (59%) and fear for an allergic reaction (24%). Five risk factors for long-term reintroduction failure were found: if culprit food was not one of the 13 EU regulated allergens, reintroduction failure at short-term, atypical symptoms during FC, a lower quality of life and a higher state anxiety.CONCLUSIONS AND CLINICAL RELEVANCE:Reintroduction failure after negative FCs in adults is common, increases over time, and is primarily due to atypical symptoms. This stresses the need for more patient-tailored care before and after negative food challenges.cc-by-nc-sa
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Subcutaneous emphysema, pneumothorax and pneumomediastinum are well-known complications of invasive ventilation in patients with acute hypoxemic respiratory failure. We determined the incidences of air leaks that were visible on available chest images in a cohort of critically ill patients with acute hypoxemic respiratory failure due to coronavirus disease of 2019 (COVID-19) in a single-center cohort in the Netherlands. A total of 712 chest images from 154 patients were re-evaluated by a multidisciplinary team of independent assessors; there was a median of three (2–5) chest radiographs and a median of one (1–2) chest CT scans per patient. The incidences of subcutaneous emphysema, pneumothoraxes and pneumomediastinum present in 13 patients (8.4%) were 4.5%, 4.5%, and 3.9%. The median first day of the presence of an air leak was 18 (2–21) days after arrival in the ICU and 18 (9–22)days after the start of invasive ventilation. We conclude that the incidence of air leaks was high in this cohort of COVID-19 patients, but it was fairly comparable with what was previously reported in patients with acute hypoxemic respiratory failure in the pre-COVID-19 era.
In the past decades, we have faced an increase in the digitization, digitalization, and digital transformation of our work and daily life. Breakthroughs of digital technologies in fields such as artificial intelligence, telecommunications, and data science bring solutions for large societal questions but also pose a new challenge: how to equip our (future)workforce with the necessary digital skills, knowledge, and mindset to respond to and drive digital transformation?Developing and supporting our human capital is paramount and failure to do so may leave us behind on individual (digital divide), organizational (economic disadvantages), and societal level (failure in addressing grand societal challenges). Digital transformation necessitates continuous learning approaches and scaffolding of interdisciplinary collaboration and innovation practices that match complex real-world problems. Research and industry have advocated for setting up learning communities as a space in which (future) professionals of different backgrounds can work, learn, and innovate together. However, insights into how and under which circumstances learning communities contribute to accelerated learning and innovation for digital transformation are lacking. In this project, we will study 13 existing and developing learning communities that work on challenges related to digital transformation to understand their working mechanisms. We will develop a wide variety of methods and tools to support learning communities and integrate these in a Learning Communities Incubator. These insights, methods and tools will result in more effective learning communities that will eventually (a) increase the potential of human capital to innovate and (b) accelerate the innovation for digital transformation
Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection. The validated product of the experiment will be tested on the monument of Fraeylemaborg.
The Ph.D. candidate will investigate the seismic response of connection details frequently used in traditional Dutch construction practice, specifically in the Groningen area. The research will focus on the experimental and numerical definition of the complete load-deflection behaviour of each considered connection; specifically, the tests will aim at identifying stiffness, strength, ductility, and dissipative behaviour of the connections. The experiments will be conducted on scaled or full-scale components that properly resemble the as-built and retrofitted as well connection details. The tests will involve monotonic and cyclic loading protocols to be able to define the load and displacement response of the connection to reversal loads, such as earthquakes, as well as the development of failure mechanisms under such loading cases. Possibly, also dynamic tests will be performed. Numerical models will be created and calibrated versus the experimental findings. Characteristic hysteretic behaviours of the examined connection types will be provided for the use of engineers and researchers.
