The current study examines how organizational career management – i.e. activities undertaken by schools in order to plan and manage teachers’ careers – relates to teachers’ career self-management – i.e. teachers steering their careers by means of searching for opportunities, networking, or seeking supervisory support. Moreover, it examines the mediating roles of occupational self-efficacy and learning goal orientation in this relationship. Mediation analysis in SPSS, using the PROCESS macro of survey data from 220 Dutch secondary school teachers, showed that positive relationships between organizational career management and career self-management were mediated by occupational self-efficacy and learning goal orientation.
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Background: Patient participation and goal setting appear to be difficult in daily physiotherapy practice, and practical methods are lacking. An existing patient-specific instrument, Patient-Specific Complaints (PSC), was therefore optimized into a new Patient Specific Goal-setting method (PSG). The aims of this study were to examine the feasibility of the PSG in daily physiotherapy practice, and to explore the potential impact of the new method. Methods: We conducted a process evaluation within a non-controlled intervention study. Community-based physiotherapists were instructed on how to work with the PSG in three group training sessions. The PSG is a six-step method embedded across the physiotherapy process, in which patients are stimulated to participate in the goal-setting process by: identifying problematic activities, prioritizing them, scoring their abilities, setting goals, planning and evaluating. Quantitative and qualitative data were collected among patients and physiotherapists by recording consultations and assessing patient files, questionnaires and written reflection reports. Results: Data were collected from 51 physiotherapists and 218 patients, and 38 recordings and 219 patient files were analysed. The PSG steps were performed as intended, but the ‘setting goals’ and ‘planning treatment’ steps were not performed in detail. The patients and physiotherapists were positive about the method, and the physiotherapists perceived increased patient participation. They became aware of the importance of engaging patients in a dialogue, instead of focusing on gathering information. The lack of integration in the electronic patient system was a major barrier for optimal use in practice. Although the self-reported actual use of the PSG, i.e. informing and involving patients, and client-centred competences had improved, this was not completely confirmed by the objectively observed behaviour. Conclusion: The PSG is a feasible method and tends to have impact on increasing patient participation in the goal-setting process. However, its full potential for shared goal setting has not been utilized yet. More implementation effort is needed to achieve the required behaviour change and a truly client-centred attitude, to make physiotherapists totally ready for shared goal setting.
In dynamic and competitive environment, the importance of innovation is accepted as a necessary ingredients for firms to create value and sustain competitive advantage. However, very little empirical research has specifically addressed to what extent different kinds of innovation rely on specific knowledge management processes and entrepreneurial orientation. The objective of this study is to identify the different types of innovation that are predominant in companies, and how to facilitate different types of innovation activities. A questionnaire survey was conducted and 169 valid replies were received. This research analyzes the relationship among knowledge management processes, as well as entrepreneurial orientation and different types of innovation. The results from an empirical survey study reveal that organizations facilitate different types of innovation (i.e., administrative versus technical innovation) through entrepreneurial orientation and knowledge management process (i.e., knowledge acquisition, knowledge sharing and knowledge application). The results also show that the partial mediating role of knowledge management processes in the relationship between entrepreneurial orientation and different types of innovation.
MULTIFILE
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
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 specific objective of HyScaling is to achieve a 25-30% cost reduction for levelized cost of hydrogen. This cost reduction will be achieved in 2030 when the HyScaling innovations have been fully implemented. HyScaling develops novel hardware (such as stacks & cell components), low-cost manufacturing processes, optimized integrated system designs and advanced operating and control strategies. In addition to the goal of accelerating implementation of hydrogen to decarbonize energy-intensive industry, HyScaling is built around industrial partners who are aiming to build a business on the HyScaling innovations. These include novel components for electrolysers (from catalysts to membranes, from electrode architectures to novel coatings) as well as electrolyser stacks and systems for different applications. For some innovations (e.g. a coating from IonBond, an electrode design from Veco) the consortium aims at starting commercialisation before the end of the program. A unique characteristic of the HyScaling program is the orientation on Use Cases. In addition to partners representing the Dutch manufacturing industry, end-users and technology providers are partner in the consortium. This enables the consortium to develop the electrolyser technology specifically for different applications. In order to be able to come to an assessment of the market for electrolysers and components, the use cases also include decentralized energy systems.Projectpartners:Nouryon, Tejin, Danieli Corus, VDL, Hauzer, VECO, lonbond, Fluor, Frames, Magneto, VONK, Borit, Delft IMP, ZEF, MTSA, SALD, Dotx control, Hydron Energy, MX, Polymers, VSL, Fraunhofer IPT, TNO, TU Delft, TU Eindhoven, ISPT, FMC.
