Purpose: To establish age-related, normal limits of monocular and binocular spatial vision under photopic and mesopic conditions. Methods: Photopic and mesopic visual acuity (VA) and contrast thresholds (CTs) were measured with both positive and negative contrast optotypes under binocular and monocular viewing conditions using the Acuity-Plus (AP) test. The experiments were carried out on participants (age range from 10 to 86 years), who met pre-established, normal sight criteria. Mean and ± 2.5σ limits were calculated within each 5-year subgroup. A biologically meaningful model was then fitted to predict mean values and upper and lower threshold limits for VA and CT as a function of age. The best-fit model parameters describe normal aging of spatial vision for each of the 16 experimental conditions investigated. Results: Out of the 382 participants recruited for this study, 285 participants passed the selection criteria for normal aging. Log transforms were applied to ensure approximate normal distributions. Outliers were also removed for each of the 16 stimulus conditions investigated based on the ±2.5σ limit criterion. VA, CTs and the overall variability were found to be age-invariant up to ~50 years in the photopic condition. A lower, age-invariant limit of ~30 years was more appropriate for the mesopic range with a gradual, but accelerating increase in both mean thresholds and intersubject variability above this age. Binocular thresholds were smaller and much less variable when compared to the thresholds measured in either eye. Results with negative contrast optotypes were significantly better than the corresponding results measured with positive contrast (p < 0.004). Conclusions: This project has established the expected age limits of spatial vision for monocular and binocular viewing under photopic and high mesopic lighting with both positive and negative contrast optotypes using a single test, which can be implemented either in the clinic or in an occupational setting.
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Educational institutions in higher education encounter different thresholds when scaling up to institution-wide learning analytics. This doctoral research focuses on designing a model of capabilities that institutions need to develop in order to remove these barriers and thus maximise the benefits of learning analytics.
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This study evaluates the maximum theoretical exposure to radiofrequency (RF) electromag- netic fields (EMFs) from a Fifth-generation (5G) New Radio (NR) base station (BS) while using four commonly used mobile applications: YouTube for video streaming, WhatsApp for voice calls, Instagram for posting pictures and videos, and running a Video game. Three factors that might affect exposure, i.e., distance of the measurement positions from the BS, measurement time, and induced traffic, were examined. Exposure was assessed through both instantaneous and time-averaged extrapolated field strengths using the Maximum Power Extrapolation (MPE) method. The former was calculated for every measured SS-RSRP (Secondary Synchronization Reference Signal Received Power) power sample obtained with a sampling resolution of 1 second, whereas the latter was obtained using a 1-min moving average applied on the applications’ instantaneous extrapolated field strengths datasets. Regarding distance, two measurement positions (MPs) were selected: MP1 at 56 meters and MP2 at 170 meters. Next, considering the measurement time, all mobile application tests were initially set to run for 30 minutes at both MPs, whereas the video streaming test (YouTube) was run for an additional 150 minutes to investigate the temporal evolution of field strengths. Considering the traffic, throughput data vs. both instantaneous and time-averaged extrapolated field strengths were observed for all four mobile applications. In addition, at MP1, a 30-minute test without a User Equipment (UE) device was conducted to analyze exposure levels in the absence of induced traffic. The findings indicated that the estimated field strengths for mobile applications varied. It was observed that distance and time had a more significant impact than the volume of data traffic generated (throughput). Notably, the exposure levels in all tests were considerably lower than the public exposure thresholds set by the ICNIRP guidelines.INDEX TERMS 5G NR, C-band, human exposure assessment, mobile applications, traffic data, maximum extrapolation method, RF-EMF.
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Clinical decision support systems (CDSSs) have gained prominence in health care, aiding professionals in decision-making and improving patient outcomes. While physicians often use CDSSs for diagnosis and treatment optimization, nurses rely on these systems for tasks such as patient monitoring, prioritization, and care planning. In nursing practice, CDSSs can assist with timely detection of clinical deterioration, support infection control, and streamline care documentation. Despite their potential, the adoption and use of CDSSs by nurses face diverse challenges. Barriers such as alarm fatigue, limited usability, lack of integration with workflows, and insufficient training continue to undermine effective implementation. In contrast to the relatively extensive body of research on CDSS use by physicians, studies focusing on nurses remain limited, leaving a gap in understanding the unique facilitators and barriers they encounter. This study aimed to explore the facilitators and barriers influencing the adoption and use of CDSSs by nurses in hospitals, using an extended Fit Between Individuals, Tasks, and Technology (FITT) framework.
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Equine-Assisted Services (EAS) offer many benefits for people with intellectual or physical disabilities. As these services grow in popularity, ensuring the welfare of the horses involved is crucial. This study explored the horses’ mood state during equine-assisted coaching and therapeutic riding sessions, focusing on factors like session length, the horse’s personality, and care practices.Keywords: horse–human interaction; welfare; equine-assisted services; health and safety; affective states
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Population ageing has been a focus of research since the 1960s (Michael et al. 2006), and it has become a domain of international discussions, debates and research throughout a myriad of disciplines including housing, urban planning and real estate (Buffel and Phillipson 2016, van Bronswijk 2015, Kort 2017). Kazak et al. (2017) described how the ageing population has a profound impact on the real estate market, which is transforming in terms of availability of retirement accommodation for older people including accessibility, adaptability, and the availability of single-floor dwellings. Older people usually have a strong connection with the environment they understand and know well (van Hoof et al. 2016), enabling them to spend the latter years of their life in a familiar setting, which, in turn, influences their self-confidence, independence and the potential to successfully age in place. Older people are encouraged to continue living in their homes a familiar environment to them, instead of moving to an institutional care facility, and this is referred to as “ageing-in-place” (van Hoof 2010). This can be supported by creating a functional and spatial structure of cities that are friendly to older people (van Hoof et al. 2018, van Hoof and Kazak 2018). In the domain of environmental design, a series of home modifications can be identified. The most frequently encountered measures in and around the home are adaptations to improve the accessibility of the home (i.e., removal of barriers such as thresholds, installation of stair lifts in multi-storey homes, and the replacement of bath tubs by walk-in showers,). Separately from these expensive measures and adaptations, simple handgrips can improve the accessibility, safety and mobility of older people (van Hoof et al. 2010, van Hoof et al. 2013). A further concern that should be considered within the living environment is the lack of storage space for wheeled walkers and mobility scooters (including a place to charge batteries) whilst living in an apartment block with limited space to manoeuvre on corridors (Kazak et al. 2017). However, with increasing demands for care, it is not always possible to remain living in one’s own home and moving into a residential or nursing facility is the only remaining option; whereby, specialist and/or nursing care can be accessed and provided in these living environments (van Hoof et al. 2009). Policy principles within long-term care aim to provide a home from home environment for their residents (Moise et al. 2004). Several specialised housing models have been developed in order to facilitate this person-centred care approach, as more traditional institutional settings often do not match with the new holistic and therapeutic goals (Verbeek 2017). Radical alterations have been made in comparison with traditional nursing homes, implementing changes in the organisational, physical and social environment of settings (Verbeek et al. 2009, van Hoof et al. 2009). For example, smaller groups of older people (six to seven persons) form a household, with nursing staff having integrated tasks, including assistance with activities of daily living, preparing meals, organising activities and doing household chores together with residents. Daily life is mainly determined by residents and nursing staff, and the physical environment resembles an archetypal house. With this distinct increase and popular notion of the role real estate plays in ageing-in-place and living well in old age, there is also a shifting focus regarding participation, activation, and helping each other. Home modifications and the home environment itself have a profound influence on the care provided and received at home. In short, the fewer barriers there are at home, the easier and less onerous responsibilities placed on the family carer(s) (Duijnstee 1992). Family carers themselves need such environmental interventions that support care, and a sense of community and belonging. Enabling one to age-in-place and to successfully age requires more than a simple occupational therapeutic approach of environmental interventions. It requires innovative new housing encompassing suitable technology arrangements that can facilitate and enable older adults to live comfortably into old age, preferably with others and offer family members (i.e., children, grandchildren and spouse). Furthermore, interconnecting technology into such environments can offer family members the option and opportunity to monitor their loved one remotely whilst all actors know there are additional safety barriers in place. This chapter discusses and provides innovative examples from a Dutch social housing association and their practices, which illustrates a new approach to environmental design that focuses more on building new communities in conjunction with the building itself, as opposed to the occupational therapeutic approaches and environmental support. First, we take a closer look at why we care for each other, which is the basis of the participation society, in which we must look after people who are near to us. This should ideally be at the basis of new housing arrangements -in which people are stimulated to meet, engage, survey and care- that social housing associations are developing, retrofitting and developing.
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This paper reports on the first stage of a research project1) that aims to incorporate objective measures of physical activity into health and lifestyle surveys. Physical activity is typically measured with questionnaires that are known to have measurement issues, and specifically, overestimate the amount of physical activity of the population. In a lab setting, 40 participants wore four different sensors on five different body parts, while performing various activities (sitting, standing, stepping with two intensities, bicycling with two intensities, walking stairs and jumping). During the first four activities, energy expenditure was measured by monitoring heart rate and the gas volume of in‐ and expired O2 and CO2. Participants subsequently wore two sensor systems (the ActivPAL on the thigh and the UKK on the waist) for a week. They also kept a diary keeping track of their physical activities, work and travel hours. Machine learning algorithms were trained with different methods to determine which sensor and which method was best able to differentiate the various activities and the intensity with which they were performed. It was found that the ActivPAL had the highest overall accuracy, possibly because the data generated on the upper tigh seems to be best distinguishing between different types of activities and therefore led to the highest accuracy. Accuracy could be slightly increased by including measures of heartrate. For recognizing intensity, three different measures were compared: allocation of MET values to activities (used by ActivPAL), median absolute deviation, and heart rate. It turns out that each method has merits and disadvantages, but median absolute deviation seems to be the most promishing metric. The search for the best method of gauging intensity is still ongoing. Subsequently, the algorithms developed for the lab data were used to determine physical activity in the week people wore the devices during their everyday activities. It quickly turned out that the models are far from ready to be used on free living data. Two approaches are suggested to remedy this: additional research with meticulously labelled free living data, e.g., by combining a Time Use Survey with accelerometer measurements. The second is to focus on better determining intensity of movement, e.g., with the help of unsupervised pattern recognition techniques. Accuracy was but one of the requirements for choosing a sensor system for subsequent research and ultimate implementation of sensor measurement in health surveys. Sensor position on the body, wearability, costs, usability, flexibility of analysis, response, and adherence to protocol equally determine the choice for a sensor. Also from these additional points of view, the activPAL is our sensor of choice.
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Background: Accurate measurement of health literacy is essential to improve accessibility and effectiveness of health care and prevention. One measure frequently applied in international research is the Short Assessment of Health Literacy (SAHL). While the Dutch SAHL (SAHL-D) has proven to be valid and reliable, its administration is time consuming and burdensome for participants. Our aim was to further validate, strengthen and shorten the SAHL-D using Rasch analysis. Methods: Available cross-sectional SAHL-D data was used from adult samples (N = 1231) to assess unidimensionality, local independence, item fit, person fit, item hierarchy, scale targeting, precision (person reliability and person separation), and presence of differential item functioning (DIF) depending on age, gender, education and study sample. Results: Thirteen items for a short form were selected based on item fit and DIF, and scale properties were compared between the two forms. The long form had several items with DIF for age, gender, educational level and study sample. Both forms showed lower measurement precision at higher health literacy levels. Conclusions: The findings support the validity and reliability of the SAHL-D for the long form and the short form, which can be used for a rapid assessment of health literacy in research and clinical practice.
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Introduction: Sensor-feedback systems can be used to support people after stroke during independent practice of gait. The main aim of the study was to describe the user-centred approach to (re)design the user interface of the sensor feedback system “Stappy” for people after stroke, and share the deliverables and key observations from this process. Methods: The user-centred approach was structured around four phases (the discovery, definition, development and delivery phase) which were fundamental to the design process. Fifteen participants with cognitive and/or physical limitations participated (10 women, 2/3 older than 65). Prototypes were evaluated in multiple test rounds, consisting of 2–7 individual test sessions. Results: Seven deliverables were created: a list of design requirements, a personae, a user flow, a low-, medium- and high-fidelity prototype and the character “Stappy”. The first six deliverables were necessary tools to design the user interface, whereas the character was a solution resulting from this design process. Key observations related to “readability and contrast of visual information”, “understanding and remembering information”, “physical limitations” were confirmed by and “empathy” was additionally derived from the design process. Conclusions: The study offers a structured methodology resulting in deliverables and key observations, which can be used to (re)design meaningful user interfaces for people after stroke. Additionally, the study provides a technique that may promote “empathy” through the creation of the character Stappy. The description may provide guidance for health care professionals, researchers or designers in future user interface design projects in which existing products are redesigned for people after stroke.
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Introduction: Previous longitudinal studies indicate that physical activity (PA) significantly declines from primary-to secondary school, and report both changes in individual and environmental determinants of PA. In order to understand this transition and to prevent this negative trend, it is important to gather contextually rich data on possible mechanisms that drive this decline. Therefore, the aim of this study was to investigate changes of PA patterns in transition between primary and secondary school, and to add domain-specific insights of how, where, and when these changes occur. Methods: In total, 175 children participated in a 7-day accelerometer- and Global Positioning System (GPS) protocol at their last year of primary and their first year of secondary school. GPS data-points were overlaid with Geographical Information Systems (GIS) data using ArcGIS 10.1 software. Based on the GPS locations of individual data-points, we identified child’s PA at home, school, local sports grounds, shopping centers, and other locations. Also, trips in active and passive transport were identified according to previously validated GPS speed-algorithms. Longitudinal multi-level linear mixed models were fitted adjusting for age, gender, meteorological circumstances, and the nested structure of days within children and children within schools. Outcome measures were minutes spent in light PA and moderate-to-vigorous PA, specified for the time-segments before school, during school, after school and weekend days. Results: Total PA significantly declined from primary to secondary school. Although transport-related PA increased before- and during school, decreases were found for especially afterschool time spent at sports grounds and transport-related PA during weekends.
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