Background: Functional decline is common in nursing home residents. Nursing staff can help prevent this decline, by encouraging residents to be more active in functional activities. Questionnaires measuring the extent to which nursing staff encourage functional activity among residents are lacking. In addition, there are no measurement instruments to gain insight into nursing staff perceived barriers and facilitators to this behavior. The aim of this study was to develop, and study the usability, of the MAastrIcht Nurses Activities INventory (MAINtAIN), an inventory assessing a) the extent to which nursing staff perceive to perform behaviors that optimize and maintain functional activity among nursing home residents and b) the perceived barriers and facilitators related to this behavior. Methods: Using a mixed-methods approach the MAINtAIN was developed and its usability was studied. Development was based on literature, expert opinions, focus group (N = 3) and individual interviews (N = 14) with residents and staff from nine nursing homes in the Netherlands. Usability was studied in a cross-sectional study with 37 nurses and certified nurse assistants; data were analyzed using descriptive statistics. Results: Development of the MAINtAIN resulted in two distinctive parts: MAINtAIN-behaviors and MAINtAIN-barriers. MAINtAIN-behaviors, targeting nursing staff behavior to optimize and maintain functional activity, includes 19 items covering activities of daily living, household activities, and miscellaneous activities. MAINtAIN-barriers addresses the perceived barriers and facilitators related to this behavior and comprises 33 items covering barriers and facilitators related to the residents, the professionals, the social context, and the organizational and economic context. The usability study showed that the inventory was not difficult to complete, that items and response options were clear,and that the number of missing values was low. Few items showed a floor or ceiling effect. Conclusions: The newly developed inventory MAINtAIN provides a usable method for researchers and nursing homes to obtain insight into nursing staff perceived behavior in optimizing functional activity among residents and their perceived barriers and facilitators related to this behavior. Outcomes of the MAINtAIN may contribute to change in nursing staff behavior and may improve nursing care. Further research with regard to the psychometric properties of the MAINtAIN is recommended.
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During the 2024 Open Science Retreat, the Measuring Open Science team collected, reviewed, and analyzed existing research into open science practices. As a team, we developed an interactive overview of open science surveys, which may be used e.g. to reuse questionnaire items on different open science practices.
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Exergames provide a challenging opportunity for home-based training and evaluation of postural control in the elderly population, but affordable sensor technology and algorithms for assessment of whole body movement patterns in the home environment are yet to be developed. The aim of the present study was to evaluate the use of Kinect, a commonly available video game sensor, for capturing and analyzing whole body movement patterns. Healthy adults (. n=20) played a weight shifting exergame under five different conditions with varying amplitudes and speed of sway movement, while 3D positions of ten body segments were recorded in the frontal plane using Kinect and a Vicon 3D camera system. Principal Component Analysis (PCA) was used to extract and compare movement patterns and the variance in individual body segment positions explained by these patterns. Using the identified patterns, balance outcome measures based on spatiotemporal sway characteristics were computed. The results showed that both Vicon and Kinect capture >90% variance of all body segment movements within three PCs. Kinect-derived movement patterns were found to explain variance in trunk movements accurately, yet explained variance in hand and foot segments was underestimated and overestimated respectively by as much as 30%. Differences between both systems with respect to balance outcome measures range 0.3-64.3%. The results imply that Kinect provides the unique possibility of quantifying balance ability while performing complex tasks in an exergame environment.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
communicative participation, language disordersOBJECTIVE(S)/RESEARCH QUESTION(S) Speech and language therapists (SLTs) are the primary care professionals to treat language and communication disorders. Their treatment is informed by a variety of outcome measures. At present, diagnosis, monitoring of progress and evaluation are often based on performance-based and clinician-reported outcomes such as results of standardized speech, language, voice, or communication tests. These tests typically aim to capture how well the person can produce or understand language in a controlled situation, and therefore only provide limited insight in the person’s challenges in life. Performance measures do not incorporate the unobservable feelings such as a patient's effort, social embarrassment, difficulty, or confidence in communication. Nor do they address language and communication difficulties experienced by the person themselves, the impact on daily life or allow patients to set goals related to their own needs and wishes. The aim of our study is give our patients a voice and empower SLTs to incorporate their patient's perspective in planning therapy. We will Aangemaakt door ProjectNet / Generated by ProjectNet: 08-12-2020 12:072Subsidieaanvraag_digitaal / Grant Application_digitaalDossier nummer / Dossier number: 80-86900-98-041DEFINITIEFdevelop a valid and reliable patient-reported outcome measure that provides information on communicative participation of people with communication disorders and integrate this item bank in patient specific goal setting in speech and language therapy. Both the item bank and the goal setting method will be adapted in cocreation with patients to enable access for people with communication difficulties.STUDY DESIGN Mixed methods research design following the MRC guidance for process evaluation of complex interventions, using PROMIS methodology including psychometric evaluation and an iterative user-centered design with qualitative co-creation methods to develop accessible items and the goal setting method.RESEARCH POPULATION Children, adolescents and adults with speech, language, hearing, and voice disorders.OUTCOME MEASURES An online patient-reported outcome measure on communicative participation, the Communicative Participation Item Bank (CPIB), CPIB items that are accessible for people with language understanding difficulties, a communicative-participation person-specific goal setting method developed with speech and language therapists and patients and tested on usability and feasibility in clinical practice, and a course for SLTs explaining the use of the goal-setting method in their clinical reasoning process.RELEVANCE This study answers one of the prioritized questions in the call for SLTs to systematically and reliably incorporate the clients’ perspective in their daily practice to improve the quality of SLT services. At present patient reported outcomes play only a small role in speech and language therapy because 1) measures (PROMS) are often invalid, not implemented and unsuitable for clinical practice and 2) there is a knowledge gap in how to capture and interpret outcomes from persons with language disorders.
