Background: Research into termination of long-term psychosocial treatment of mental disorders is scarce. Yearly 25% of people in Dutch mental health services receive long-term treatment. They account for many people, contacts, and costs. Although relevant in different health care systems, (dis)continuation is particularly problematic under universal health care coverage when secondary services lack a fixed (financially determined) endpoint. Substantial, unaccounted, differences in treatment duration exist between services. Understanding of underlying decisional processes may result in improved decision making, efficient allocation of scarce resources, and more personalized treatment.
Objective: To construct the underlying value structure of shared decision making (SDM) models. Method: We included previously identified SDM models (n = 40) and 15 additional ones. Using a thematic analysis, we coded the data using Schwartz’s value theory to define values in SDM and to investigate value relations. Results: We identified and defined eight values and developed three themes based on their relations: shared control, a safe and supportive environment, and decisions tailored to patients. We constructed a value structure based on the value relations and themes: the interplay of healthcare professionals’ (HCPs) and patients’ skills [Achievement], support for a patient [Benevolence], and a good relationship between HCP and patient [Security] all facilitate patients’ autonomy [Self-Direction]. These values enable a more balanced relationship between HCP and patient and tailored decision making [Universalism]. Conclusion: SDM can be realized by an interplay of values. The values Benevolence and Security deserve more explicit attention, and may especially increase vulnerable patients’ Self-Direction. Practice implications: This value structure enables a comparison of values underlying SDM with those of specific populations, facilitating the incorporation of patients’ values into treatment decision making. It may also inform the development of SDM measures, interventions, education programs, and HCPs when practicing.
Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases. We highlight the significance of predictive objective tools that should be deployed by contemporary FRM models. We also report the need for utilization of scientific-based tools for predictive FRM, in which objective sleep quality and neurocognitive assessment should be the core aspect. We note the period of restructuring ahead as an opportunity for operators to rethink and restructure their FRM.
The objective of the SIA KIEM proposal Capturing Value is to understand financial decision making and capturing value as a logical step in the conceptual and realization phase of creative products. We will explore the narrative of reasoning and making choices in the use of different financial instruments by creative professionals. These narratives are telling about the values creative professionals attach to financial decision making and how these influence the choice of financial instruments. Most research focusses either on the (non)availability of financial instruments or on the use of these instruments. This research proposal focusses on the missing link: how do creative professionals reason when confronted with making financial decisions? Which options do they consider and how are these influenced by their attitude towards and knowledge of various formal and informal financial instruments? The project is a first step to develop a bigger and international research proposal on the way artists and creatives capture the financial value of their creations.
Low back pain is the leading cause of disability worldwide and a significant contributor to work incapacity. Although effective therapeutic options are scarce, exercises supervised by a physiotherapist have shown to be effective. However, the effects found in research studies tend to be small, likely due to the heterogeneous nature of patients' complaints and movement limitations. Personalized treatment is necessary as a 'one-size-fits-all' approach is not sufficient. High-tech solutions consisting of motions sensors supported by artificial intelligence will facilitate physiotherapists to achieve this goal. To date, physiotherapists use questionnaires and physical examinations, which provide subjective results and therefore limited support for treatment decisions. Objective measurement data obtained by motion sensors can help to determine abnormal movement patterns. This information may be crucial in evaluating the prognosis and designing the physiotherapy treatment plan. The proposed study is a small cohort study (n=30) that involves low back pain patients visiting a physiotherapist and performing simple movement tasks such as walking and repeated forward bending. The movements will be recorded using sensors that estimate orientation from accelerations, angular velocities and magnetometer data. Participants complete questionnaires about their pain and functioning before and after treatment. Artificial analysis techniques will be used to link the sensor and questionnaire data to identify clinically relevant subgroups based on movement patterns, and to determine if there are differences in prognosis between these subgroups that serve as a starting point of personalized treatments. This pilot study aims to investigate the potential benefits of using motion sensors to personalize the treatment of low back pain. It serves as a foundation for future research into the use of motion sensors in the treatment of low back pain and other musculoskeletal or neurological movement disorders.
The Dutch floriculture is globally leading, and its products, knowledge and skills are important export products. New challenges in the European research agenda include sustainable use of raw materials such as fertilizer, water and energy, and limiting the use of pesticides. Greenhouse growers however have little control over crop growth conditions in the greenhouse at individual plant level. The purpose of this project, ‘HiPerGreen’, is to provide greenhouse owners with new methods to monitor the crop growth conditions in their greenhouse at plant level, compare the measured growth conditions and the measured growth with expected conditions and expected growth, to point out areas with deviations, recommend counter-measures and ultimately to increase their crop yield. The main research question is: How can we gather, process and present greenhouse crop growth parameters over large scale greenhouses in an economical way and ultimately improve crop yield? To provide an answer to this question, a team of university researchers and companies will cooperate in this applied research project to cover several different fields of expertise The application target is floriculture: the production of ornamental pot plants and cut flowers. Participating companies are engaged in the cultivation of pot plans, flowers and suppliers of greenhouse technology. Most of the parties fall in the SME (MKB) category, in line with the RAAK MKB objectives.Finally, the Demokwekerij and Hortipoint (the publisher of the international newsletter on floriculture) are closely involved. The project will develop new knowledge for a smart and rugged data infrastructure for growth monitoring and growth modeling in the greenhouse. In total the project will involve approximately 12 (teacher) researchers from the universities and about 60 students, who will work in the form of internships and undergraduate studies of interesting questions directly from the participating companies.
