Background: Dementia care at home often involves decisions in which the caregiver must weigh safety concerns with respect for autonomy. These dilemmas can lead to situations where caregivers provide care against the will of persons living with dementia, referred to as involuntary treatment. To prevent this, insight is needed into how family caregivers of persons living with dementia deal with care situations that can lead to involuntary treatment. Objective: To identify and describe family caregivers’ experiences regarding care decisions for situations (...) that can lead to involuntary treatment use in persons living with dementia at home. Research design: A qualitative descriptive interview design. Data were analysed using the Qualitative Analysis Guide of Leuven. Participants and research context: A total of 10 family caregivers providing care for 13 persons living with dementia participated in in-depth semi-structured interviews. Participants were recruited by registered nurses via purposive sampling. Ethical consideration: The study protocol was approved by the Ethics Committee of the University Hospitals Leuven and the Medical Ethical Test Committee Zuyderland. Findings: Family caregivers experience the decision-making process concerning care dilemmas that can lead to involuntary treatment as complicated, stressful and exhausting. Although they consider safety and autonomy as important values, they struggle with finding the right balance between them. Due to the progressive and unpredictable nature of dementia, they are constantly seeking solutions while they adapt to new situations. Family caregivers feel responsible and experience social pressure for the safety of persons living with dementia. They may be blamed if something adverse happens to the persons living with dementia, which increases an already stressful situation. Their experience is influenced by characteristics of the care triad such as practical and emotional support, knowledge, and previous experiences. Discussion and conclusion: To prevent involuntary treatment, professionals need to proactively inform family caregivers, and they need to support each other in dealing with complex care situations. (shrink)
The implementation of a National Ecological Network poses a significant challenge to the Dutch government. The establishment of this ecological network has led to conflicts among various interest groups in the public sphere, each of which defends its own interests. In this struggle for recognition communication fulfils an important role. This article contends that the discourse about nature is driven by deep frames, is comprised of values and is rooted in world-views. The insight that worldviews play a role elucidates the (...) various positions in the debate and shows normative dimensions in communication. This article argues that the network society, more than ever, requires the government to be explicit about its normative choices. (shrink)
A lot of research has been done on the detection of mental workload using various bio-signals. Recently, deep learning has allowed for novel methods and results. A plethora of measurement modalities have proven to be valuable in this task, yet studies currently often only use a single modality to classify MWL. The goal of this research was to classify perceived mental workload using a deep neural network that flexibly makes use of multiple modalities, in order to allow for feature sharing (...) between modalities. To achieve this goal, an experiment was conducted in which MWL was simulated with the help of verbal logic puzzles. The puzzles came in five levels of difficulty and were presented in a random order. Participants had 1 h to solve as many puzzles as they could. Between puzzles, they gave a difficulty rating between 1 and 7, seven being the highest difficulty. Galvanic skin response, photoplethysmograms, functional near-infrared spectrograms and eye movements were collected simultaneously using LabStreamingLayer. Marker information from the puzzles was also streamed on LSL. We designed and evaluated a novel intermediate fusion multimodal DNN for the classification of PMWL using the aforementioned four modalities. Two main criteria that guided the design and implementation of our DNN are modularity and generalisability. We were able to classify PMWL within-level accurate on a seven-level workload scale using the aforementioned modalities. The model architecture allows for easy addition and removal of modalities without major structural implications because of the modular nature of the design. Furthermore, we showed that our neural network performed better when using multiple modalities, as opposed to a single modality. The dataset and code used in this paper are openly available. (shrink)
Review of book: Bondecka-Krzykowska I., Brzeziński K.M., Bulińska-Stangrecka H., et al., Przedmioty wirtualne, P. Stacewicz, B. Skowron, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2019, pp. 135.