Purpose (1) To investigate the differences in the course of participation up to one year after stroke between distinct movement behavior patterns identified directly after discharge to the home setting, and (2) to investigate the longitudinal association between the development of movement behavior patterns over time and participation after stroke. Materials and methods 200 individuals with a first-ever stroke were assessed directly after discharge to the home setting, at six months and at one year. The Participation domain of the Stroke Impact Scale 3.0 was used to measure participation. Movement behavior was objectified using accelerometry for 14 days. Participants were categorized into three distinct movement behavior patterns: sedentary exercisers, sedentary movers and sedentary prolongers. Generalized estimating equations (GEE) were performed. Results People who were classified as sedentary prolongers directly after discharge was associated with a worse course of participation up to one year after stroke. The development of sedentary prolongers over time was also associated with worse participation compared to sedentary exercisers. Conclusions The course of participation after stroke differs across distinct movement behavior patterns after discharge to the home setting. Highly sedentary and inactive people with stroke are at risk for restrictions in participation over time. Implications for rehabilitation The course of participation in people with a first-ever stroke up to one year after discharge to the home setting differed based on three distinct movement behavior patterns, i.e., sedentary exercisers, sedentary movers and sedentary prolongers. Early identification of highly sedentary and inactive people with stroke after discharge to the home setting is important, as sedentary prolongers are at risk for restrictions in participation over time. Supporting people with stroke to adapt and maintain a healthy movement behavior after discharge to the home setting could prevent potential long-term restrictions in participation.
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Studying images on social media introduces several challenges that relate to the size of datasets and the different meaning-making grammars of social visuality; or as aptly pointed out by others in the field, it means ‘studying the qualitative on a quantitative scale’. Although cultural analytics provides an automated process through which patterns can be detected in large numbers of images, this methodology doesn’t account for other modalities of the image than the image itself. However, images circulating social media can (and should) be analyzed on the level of their audience as the latter is co-creating the meaning of images. Bridging the study of platform affordances and affect theory, this paper presents a novel methodology that repurposes Facebook Reactions to infer collective attitudes and performative emotional expressions vis á vis images shared on the large Syrian Revolution Network public page (+2M). We found visual patterns that co-occur with certain collective combinations of buttons, displaying how socio-technical features shape the discursive frameworks of online publics.
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Supermarkets are essential urban household amenities, providing daily products, and for their social role in communities. Contrary to many other countries, including nearby ones, the Netherlands have a balanced distribution of supermarkets across villages and urban neighbourhoods. However, spatial supermarket patterns, are subject to influential developments. First, due to economies of scale, there is a tendency for supermarkets to increase their catchment areas and to disappear from peripheral villages. Second, supermarkets are now mainly located in residential areas, although the urban periphery appears to be attractive for the retail sector, perhaps including the rise of hypermarkets. Third, today, online grocery shopping is still lagging far behind on other online shopping products, but a breaks through will dilute population support for in-store supermarkets and can lead to dramatic ‘game changer’ shifts with major spatial and social effects. These three important trends will reinforce each other. Consequences are of natural community meeting places at the expense of social cohesion; reduced accessibility for daily products, leading to more travel, often by car; increasing delivery flows; real estate vacancies, and increasing suburban demand increase for retail and logistics. Expected changes in supermarket patterns require understanding, but academic literature on OGS is still scarce, and does hardly address household behaviour in changing spatial constellations. We develop likely spatial supermarket patterns, and model the consequences for travel demand, social cohesion and real estate demand, as well as the distribution between online and in-store grocery shopping, by developing a stated preference experiment, among Dutch households.
Despite the recognized benefits of running for promoting overall health, its widespread adoption faces a significant challenge due to high injury rates. In 2022, runners reported 660,000 injuries, constituting 13% of the total 5.1 million sports-related injuries in the Netherlands. This translates to a disturbing average of 5.5 injuries per 1,000 hours of running, significantly higher than other sports such as fitness (1.5 injuries per 1,000 hours). Moreover, running serves as the foundation of locomotion in various sports. This emphasizes the need for targeted injury prevention strategies and rehabilitation measures. Recognizing this social issue, wearable technologies have the potential to improve motor learning, reduce injury risks, and optimize overall running performance. However, unlocking their full potential requires a nuanced understanding of the information conveyed to runners. To address this, a collaborative project merges Movella’s motion capture technology with Saxion’s expertise in e-textiles and user-centered design. The result is the development of a smart garment with accurate motion capture technology and personalized haptic feedback. By integrating both sensor and actuator technology, feedback can be provided to communicate effective risks and intuitive directional information from a user-centered perspective, leaving visual and auditory cues available for other tasks. This exploratory project aims to prioritize wearability by focusing on robust sensor and actuator fixation, a suitable vibration intensity and responsiveness of the system. The developed prototype is used to identify appropriate body locations for vibrotactile stimulation, refine running styles and to design effective vibration patterns with the overarching objective to promote motor learning and reduce the risk of injuries. Ultimately, this collaboration aims to drive innovation in sports and health technology across different athletic disciplines and rehabilitation settings.
Performance feedback is an important mechanism of adaptation in learning theories, as it provides one of the motivations for organizations to learn (Pettit, Crossan, and Vera 2017). Embedded in the behavioral theory of the firm, organizational learning from performance feedback predicts the probability for organizations to change with an emphasis on organizational aspirations, which serve as a threshold against which absolute performance is evaluated (Cyert and March 1963; Greve 2003). It postulates that performance becomes a ‘problem’, or the trigger to search for alternative procedures, strategies, products and behaviors, when performance is below that threshold. This search is known as problemistic search. Missing from this body of research, is empirically grounded understanding if the characteristics of performance feedback over time matter for the triggering function of the feedback. I explore this gap. This investigation adds temporality as a dimension of the performance feedback concept guided by a worldview of ongoing change and flux where conditions and choices are not given, but made relevant by actors and enacted upon (Tsoukas and Chia 2002). The general aim of the study is to complement the current knowledge of performance feedback as a trigger for problemistic search with an explicit process temporal approach. The main question guiding this project is how temporal patterns of performance feedback influence organizational change, which I answer in four chapters, each zooming into one sub-question.First, I focus on the temporal order of performance feedback by examining performance feedback and change sequences organizations go through. In this section time is under study and the goal is to explore how feedback patterns have evolved over time, just as the change states organizations pass through. Second, I focus on the plurality of performance feedback by investigating performance feedback from multiple aspiration levels (i.e. multiple qualitatively different metrics and multiple reference points) and how over time clusters of performance feedback sequences have evolved. Next, I look into the rate and scope of change relative to performance feedback sequences and add an element of signal strength to the feedback. In the last chapter, time is a predictor (in the sequences), and, it is under study (in the timing of responses). I focus on the timing of organizational responses in relation to performance feedback sequences of multiple metrics and reference points.In sum, all chapters are guided by the timing problem of performance feedback, meaning that performance feedback does not come ‘available’ at a single point in time. Similarly to stones with unequal weight dropped in the river, performance feedback with different strength comes available at multiple points in time and it is plausible that sometimes it is considered by decision-makers as problematic and sometimes it is not, because of the sequence it is part of. Overall, the investigation is grounded in the general principles of organizational learning from performance feedback, and the concept of time as duration, sequences and timing, with a focus on specification of when things happen. The context of the study is universities of applied sciences and hotels in The Netherlands. Project partner: Tilburg University, School of Social and Behavioral Sciences, Department of Organization Studies