Objective. Hospital in Motion is a multidimensional implementation project aiming to improve movement behavior during hospitalization. The purpose of this study was to investigate the effectiveness of Hospital in Motion on movement behavior. Methods. This prospective study used a pre-implementation and post-implementation design. Hospital in Motion was conducted at 4 wards of an academic hospital in the Netherlands. In each ward, multidisciplinary teams followed a 10-month step-by-step approach, including the development and implementation of a ward-specific action plan with multiple interventions to improve movement behavior. Inpatient movement behavior was assessed before the start of the project and 1 year later using a behavioral mapping method in which patients were observed between 9:00 am and 4:00 pm. The primary outcome was the percentage of time spent lying down. In addition, sitting and moving, immobility-related complications, length of stay, discharge destination home, discharge destination rehabilitation setting, mortality, and 30-day readmissions were investigated. Differences between pre-implementation and post-implementation conditions were analyzed using the chi-square test for dichotomized variables, the Mann Whitney test for non-normal distributed data, or independent samples t test for normally distributed data. Results. Patient observations demonstrated that the primary outcome, the time spent lying down, changed from 60.1% to 52.2%. For secondary outcomes, the time spent sitting increased from 31.6% to 38.3%, and discharges to a rehabilitation setting reduced from 6 (4.4%) to 1 (0.7%). No statistical differences were found in the other secondary outcome measures. Conclusion. The implementation of the multidimensional project Hospital in Motion was associated with patients who were hospitalized spending less time lying in bed and with a reduced number of discharges to a rehabilitation setting. Impact. Inpatient movement behavior can be influenced by multidimensional interventions. Programs implementing interventions that specifically focus on improving time spent moving, in addition to decreasing time spent lying, are recommended.
Background: Development of more effective interventions for nonspecific chronic low back pain (LBP), requires a robust theoretical framework regarding mechanisms underlying the persistence of LBP. Altered movement patterns, possibly driven by pain-related cognitions, are assumed to drive pain persistence, but cogent evidence is missing. Aim: To assess variability and stability of lumbar movement patterns, during repetitive seated reaching, in people with and without LBP, and to investigate whether these movement characteristics are associated with painrelated cognitions. Methods: 60 participants were recruited, matched by age and sex (30 back-healthy and 30 with LBP). Mean age was 32.1 years (SD13.4). Mean Oswestry Disability Index-score in LBP-group was 15.7 (SD12.7). Pain-related cognitions were assessed by the ‘Pain Catastrophizing Scale’ (PCS), ‘Pain Anxiety Symptoms Scale’ (PASS) and the task-specific ‘Expected Back Strain’ scale(EBS). Participants performed a seated repetitive reaching movement (45 times), at self-selected speed. Lumbar movement patterns were assessed by an optical motion capture system recording positions of cluster markers, located on the spinous processes of S1 and T8. Movement patterns were characterized by the spatial variability (meanSD) of the lumbar Euler angles: flexion-extension, lateralbending, axial-rotation, temporal variability (CyclSD) and local dynamic stability (LDE). Differences in movement patterns, between people with and without LBP and with high and low levels of pain-related cognitions, were assessed with factorial MANOVA. Results: We found no main effect of LBP on variability and stability, but there was a significant interaction effect of group and EBS. In the LBP-group, participants with high levels of EBS, showed increased MeanSDlateral-bending (p = 0.004, η2 = 0.14), indicating a large effect. MeanSDaxial-rotation approached significance (p = 0.06). Significance: In people with LBP, spatial variability was predicted by the task-specific EBS, but not by the general measures of pain-related cognitions. These results suggest that a high level of EBS is a driver of increased spatial variability, in participants with LBP.
Background and purpose The aim of this study is to investigate changes in movement behaviors, sedentary behavior and physical activity, and to identify potential movement behavior trajectory subgroups within the first two months after discharge from the hospital to the home setting in first-time stroke patients. Methods A total of 140 participants were included. Within three weeks after discharge, participants received an accelerometer, which they wore continuously for five weeks to objectively measure movement behavior outcomes. The movement behavior outcomes of interest were the mean time spent in sedentary behavior (SB), light physical activity (LPA) and moderate to vigorous physical activity (MVPA); the mean time spent in MVPA bouts ≥ 10 minutes; and the weighted median sedentary bout. Generalized estimation equation analyses were performed to investigate overall changes in movement behavior outcomes. Latent class growth analyses were performed to identify patient subgroups of movement behavior outcome trajectories. Results In the first week, the participants spent an average, of 9.22 hours (67.03%) per day in SB, 3.87 hours (27.95%) per day in LPA and 0.70 hours (5.02%) per day in MVPA. Within the entire sample, a small but significant decrease in SB and increase in LPA were found in the first weeks in the home setting. For each movement behavior outcome variable, two or three distinctive subgroup trajectories were found. Although subgroup trajectories for each movement behavior outcome were identified, no relevant changes over time were found. Conclusion Overall, the majority of stroke survivors are highly sedentary and a substantial part is inactive in the period immediately after discharge from hospital care. Movement behavior outcomes remain fairly stable during this period, although distinctive subgroup trajectories were found for each movement behavior outcome. Future research should investigate whether movement behavior outcomes cluster in patterns.
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Creating and testing the first Brand Segmentation Model in Augmented Reality using Microsoft Hololens. Sanoma together with SAMR launched an online brand segmentation tool based on large scale research, The brand model uses several brand values divided over three axes. However they cannot be displayed clearly in a 2D model. The space of BSR Quality Planner can be seen as a 3-dimensional meaningful space that is defined by the terms used to typify the brands. The third axis concerns a behaviour-based dimension: from ‘quirky behaviour’ to ‘standardadjusted behaviour’ (respectful, tolerant, solidarity). ‘Virtual/augmented reality’ does make it possible to clearly display (and experience) 3D. The Academy for Digital Entertainment (ADE) of Breda University of Applied Sciences has created the BSR Quality Planner in Virtual Reality – as a hologram. It’s the world’s first segmentation model in AR. Breda University of Applied Sciences (professorship Digital Media Concepts) has deployed hologram technology in order to use and demonstrate the planning tool in 3D. The Microsoft HoloLens can be used to experience the model in 3D while the user still sees the actual surroundings (unlike VR, with AR the space in which the user is active remains visible). The HoloLens is wireless, so the user can easily walk around the hologram. The device is operated using finger gestures, eye movements or voice commands. On a computer screen, other people who are present can watch along with the user. Research showed the added value of the AR model.Partners:Sanoma MediaMarketResponse (SAMR)
Wildlife crime is an important driver of biodiversity loss and disrupts the social and economic activities of local communities. During the last decade, poaching of charismatic megafauna, such as elephant and rhino, has increased strongly, driving these species to the brink of extinction. Early detection of poachers will strengthen the necessary law enforcement of park rangers in their battle against poaching. Internationally, innovative, high tech solutions are sought after to prevent poaching, such as wireless sensor networks where animals function as sensors. Movement of individuals of widely abundant, non-threatened wildlife species, for example, can be remotely monitored ‘real time’ using GPS-sensors. Deviations in movement of these species can be used to indicate the presence of poachers and prevent poaching. However, the discriminative power of the present movement sensor networks is limited. Recent advancements in biosensors led to the development of instruments that can remotely measure animal behaviour and physiology. These biosensors contribute to the sensitivity and specificity of such early warning system. Moreover, miniaturization and low cost production of sensors have increased the possibilities to measure multiple animals in a herd at the same time. Incorporating data about within-herd spatial position, group size and group composition will improve the successful detection of poachers. Our objective is to develop a wireless network of multiple sensors for sensing alarm responses of ungulate herds to prevent poaching of rhinos and elephants.
To what extent does receiving information about either popular attractions or less-visited at-tractions, presented as “highlights” of the city, influence the movement of tourists to popular or less-visited attractions, and how does this differ by information channel through which the information is presented? To what extent does receiving information about either popular attractions or less-visited at-tractions, presented as “highlights” of the city, influence tourists’ experience, including their evaluations of the destination, their visit as a whole, and the specific information channel they received, and how does this differ by information channel through which the information is presented? What implementation models and financing mechanisms are available for DMO’s to spread tourists using the information channels tested, contingent on their effectiveness as measured by the previous experiment?Societal issueDestination Management Organisations (DMOs) are looking for interventions that effectively discourage tourists from visiting crowded hotspots and entice them to visit less crowded locations. Interventions like changing infrastructure, charging entrance fees and re-serving site access are either too expensive, too invasive or politically controversial. It is much easier to intervene on tourists' behaviour by informing them about alternatives.Collaborative partnersNHL Stenden, Travel with Zoey, Amsterdam and Partners, Wonderful Copenhagen, Mobidot.
