In dit artikel wordt gekeken naar de relatie tussen het gebruik van mobiele applicaties en fysieke activiteit en gezonde leefstijl. Dit is gedaan op basis van een vragenlijst onder deelnemers aan een hardloopevenement, de Dam tot Damloop. Er werden aparte analyses gedaan voor 8km lopers en 16 km lopers. Een positieve relatie werd gevonden tussen app gebruik en meer bewegen en zich gezonder voelen. App gebruik was ook positief gerelateerd aan beter voelen over zichzelf, je voelen als een atleet, anderen motiveren om te gaan hardlopen en afvallen. Voor de 16 km lopers was app gebruik gerelateerd aan gezonder eten, zich meer energieker voelen en een hogere kans om het sportgedrag vol te houden. De resultaten van dit onderzoek laten zien dat app gebruik mogelijk een ondersteunende rol kunnen hebben in de voorbereiding op een hardloopevenemen, aangezien het gezondheid en fysieke activiteit stimuleert.
Background: Recently, research focus has shifted to the combination of all 24-h movement behaviors (physical activity, sedentary behavior and sleep) instead of each behavior separately. Yet, no reliable and valid proxy-report tools exist to assess all these behaviors in 0–4-year-old children. By involving end-users (parents) and key stakeholders (researchers, professionals working with young children), this mixed-methods study aimed to 1) develop a mobile application (app)-based proxy-report tool to assess 24-h movement behaviors in 0–4-year-olds, and 2) examine its content validity. Methods: First, we used concept mapping to identify activities 0–4-year-olds engage in. Parents (n = 58) and professionals working with young children (n = 21) generated a list of activities, sorted related activities, and rated the frequency children perform these activities. Second, using multidimensional scaling and cluster analysis, we created activity categories based on the sorted activities of the participants. Third, we developed the My Little Moves app in collaboration with a software developer. Finally, we examined the content validity of the app with parents (n = 14) and researchers (n = 6) using focus groups and individual interviews. Results: The app has a time-use format in which parents proxy-report the activities of their child, using eight activity categories: personal care, eating/drinking, active transport, passive transport, playing, screen use, sitting/lying calmly, and sleeping. Categories are clarified by providing examples of children’s activities. Additionally, 1–4 follow-up questions collect information on intensity (e.g., active or calm), posture, and/or context (e.g., location) of the activity. Parents and researchers considered filling in the app as feasible, taking 10–30 min per day. The activity categories were considered comprehensive, but alternative examples for several activity categories were suggested to increase the comprehensibility and relevance. Some follow-up questions were considered less relevant. These suggestions were adopted in the second version of the My Little Moves app. Conclusions: Involving end-users and key stakeholders in the development of the My Little Moves app resulted in a tailored tool to assess 24-h movement behaviors in 0–4-year-olds with adequate content validity. Future studies are needed to evaluate other measurement properties of the app.
MULTIFILE
Abstract: The primary aim of the dissertation was to develop and evaluate a smartphone app, the WhiteTeeth app, designed to promote good oral health behaviour and oral hygiene among adolescent orthodontic patients between the ages of 12 and 16. The app's development and evaluation was guided methodically by intervention mapping (IM). Development thus starts with an analysis of the health problem and the identification of the psychosocial factors and health behaviour related to it. To identify the psychosocial factors underlying oral health behaviour in our target group, a systematic literature review with meta-analysis was conducted,a cross-sectional clinical study and semi-structured interviews. Then, to target these psychosocial factors and facilitate continuous behavioural support, various behaviour-changing techniques were incorporated into the app. The app provides feedback on users' oral health behaviour and allows users to evaluate and monitor their behaviour. Finally, a randomised controlled trial was conducted. This showed that the app had improved oral hygiene in adolescent orthodontic patients after 12 weeks.
LINK
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
The focus of the research is 'Automated Analysis of Human Performance Data'. The three interconnected main components are (i)Human Performance (ii) Monitoring Human Performance and (iii) Automated Data Analysis . Human Performance is both the process and result of the person interacting with context to engage in tasks, whereas the performance range is determined by the interaction between the person and the context. Cheap and reliable wearable sensors allow for gathering large amounts of data, which is very useful for understanding, and possibly predicting, the performance of the user. Given the amount of data generated by such sensors, manual analysis becomes infeasible; tools should be devised for performing automated analysis looking for patterns, features, and anomalies. Such tools can help transform wearable sensors into reliable high resolution devices and help experts analyse wearable sensor data in the context of human performance, and use it for diagnosis and intervention purposes. Shyr and Spisic describe Automated Data Analysis as follows: Automated data analysis provides a systematic process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. Their philosophy is to do the tedious part of the work automatically, and allow experts to focus on performing their research and applying their domain knowledge. However, automated data analysis means that the system has to teach itself to interpret interim results and do iterations. Knuth stated: Science is knowledge which we understand so well that we can teach it to a computer; and if we don't fully understand something, it is an art to deal with it.[Knuth, 1974]. The knowledge on Human Performance and its Monitoring is to be 'taught' to the system. To be able to construct automated analysis systems, an overview of the essential processes and components of these systems is needed.Knuth Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.
Coastal nourishments, where sand from offshore is placed near or at the beach, are nowadays a key coastal protection method for narrow beaches and hinterlands worldwide. Recent sea level rise projections and the increasing involvement of multiple stakeholders in adaptation strategies have resulted in a desire for nourishment solutions that fit a larger geographical scale (O 10 km) and a longer time horizon (O decades). Dutch frontrunner pilot experiments such as the Sandmotor and Ameland inlet nourishment, as well as the Hondsbossche Dunes coastal reinforcement project have all been implemented from this perspective, with the specific aim to encompass solutions that fit in a renewed climate-resilient coastal protection strategy. By capitalizing on recent large-scale nourishments, the proposed Coastal landSCAPE project C-SCAPE will employ and advance the newly developed Dynamic Adaptive Policy Pathways (DAPP) approach to construct a sustainable long-term nourishment strategy in the face of an uncertain future, linking climate and landscape scales to benefits for nature and society. Novel long-term sandy solutions will be examined using this pathways method, identifying tipping points that may exist if distinct strategies are being continued. Crucial elements for the construction of adaptive pathways are 1) a clear view on the long-term feasibility of different nourishment alternatives, and 2) solid, science-based quantification methods for integral evaluation of the social, economic, morphological and ecological outcomes of various pathways. As currently both elements are lacking, we propose to erect a Living Lab for Climate Adaptation within the C-SCAPE project. In this Living Lab, specific attention is paid to the socio-economic implications of the nourished landscape, as we examine how morphological and ecological development of the large-scale nourishment strategies and their design choices (e.g. concentrated vs alongshore uniform, subaqueous vs subaerial, geomorphological features like artificial lagoons) translate to social acceptance.
