32 resultados para wayfinding


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Well-designed indoor environments can support people’s health and welfare. In this literature review, we identify the environmental features that affect human health and wellbeing. Environmental characteristics found to influence health outcomes and/or wellbeing included: environmental safety; indoor air quality (e.g. odour and temperature); sound and noise; premises and interior design (e.g. construction materials, viewing nature and experiencing nature, windows versus no windows, light, colours, unit layout and placement of the furniture, the type of room, possibilities to control environmental elements, environmental complexity and sensory simulations, cleanliness, ergonomics and accessibility, ‛‛wayfinding’’); art, and music, among others. Indoor environments that incorporate healing elements can, for instance, reduce anxiety, lower blood pressure, lessen pain and shorten hospital stays.

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Understanding the physical characteristics of the indoor environment that affect human health and wellbeing is the key requirement underpinning the beneficial design of a healthcare facility (HCF). We reviewed and summarised physical factors of the indoor environment reported to affect human health and wellbeing in HCFs. Research materials included articles identified in a Pubmed search, guidelines, books, reports and monographs, as well as the bibliographies of review articles in the area studied. Of these, 209 publications were selected for this review. According to the literature, there is evidence that the following physical factors of the indoor environment affect the health and wellbeing of human beings in an HCF: safety, ventilation and HVAC systems, thermal environment, acoustic environment, interior layout and room type, windows (including daylight and views), nature and gardens, lighting, colour, floor covering, furniture and its placement, ergonomics, wayfinding, artworks and music. Some of these, in themselves, directly promote or hinder health and wellbeing, but the physical factors may also have numerous indirect impacts by influencing the behaviour, actions, and interactions of patients, their families and the staff members. The findings of this research enable a good understanding of the different physical factors of the indoor environment on health and wellbeing and provide a practical resource for those responsible for the design and operate the facilities as well as researchers investigating these factors. However, more studies are needed in order to inform the design of optimally beneficial indoor environments in HCFs for all user groups.

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Passengers navigating through airports can experience confusion or become lost, resulting in dissatisfaction, missed flights and flight delays. Passengers moving through airports are required to make many navigation decisions, for example to find the correct check-in desk or find the correct boarding gate. Prior experience of using the airports is likely to enable intuitive navigation, however limited research on this topic currently exists. In this paper we investigate passenger navigation by observing 30 participants at one international airport as they moved from check-in to a departure gate. The results indicate that passengers do spend time navigating intuitively through the airport, and that there is a positive correlation between intuitive navigation and airport familiarity. It was also found that participants with lower airport familiarity spend a greater percentage of overall navigation time searching and assessing/acquiring information than high familiarity participants. These findings provide evidence that passengers with higher airport familiarity have a greater understanding of the process, have a better understanding of what information to look for and use this familiarity to navigate intuitively. Findings from this research will have design implications for both current, and future airport terminals and other large spaces that people navigate through.

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Airports accommodate passengers with a range of prior experience, from frequent flyers, to passengers who fly every couple of years, to those who have never flown before. Passengers with varying levels of prior experience may use different visual elements when navigating the airport. Ensuring all passengers can navigate to the processing activities intuitively is important for passengers, airports and airlines. This paper examines how participants with Low, Medium and High airport familiarity navigate through the departures area at an Australian international airport. Three navigation activities are investigated: (i) navigating to the check-in row, (ii) navigating through the Liquids, Aerosols and Gels (LAGs) preparation area before security screening, and; (iii) navigating to either the boarding gate first or to a discretionary activity first, after exiting customs. In the three activities, differences were observed between the familiarity groups. These differences include the use of different information to locate the check-in desk, different actions when navigating through the LAG preparation area, and evidence that Low familiarity passengers have a desire to locate the boarding gate as soon as possible once through customs. This research provides evidence based design reccomendations for airports to benefit from intuitive passenger navigation.

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The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.

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Objective This prospective longitudinal study aims to determine the risk factors of wandering-related adverse consequences in community-dwelling persons with mild dementia. These adverse consequences include negative outcomes of wandering (falls, fractures, and injuries) and eloping behavior. Methods We recruited 143 dyads of persons with mild dementia and their caregivers from a veteran's hospital and memory clinic in Florida. Wandering-related adverse consequences were measured using the Revised Algase Wandering Scale – Community Version. Variables such as personality (Big Five Inventory), behavioral response to stress, gait, and balance (Tinetti Gait and Balance), wayfinding ability (Wayfinding Effectiveness Scale), and neurocognitive abilities (attention, cognition, memory, language/verbal skills, and executive functioning) were also measured. Bivariate and logistic regression analyses were performed to assess the predictors of these wandering-related adverse consequences. Results A total of 49% of the study participants had falls, fractures, and injuries due to wandering behavior, and 43.7% demonstrated eloping behaviors. Persistent walking (OR = 2.6) and poor gait (OR = 0.9) were significant predictors of negative outcomes of wandering, while persistent walking (OR = 13.2) and passivity (OR = 2.55) predicted eloping behavior. However, there were no correlations between wandering-related adverse consequences and participants' characteristics (age, gender, race, ethnicity, and education), health status (Charlson comorbidity index), or neurocognitive abilities. Conclusion Our results highlight the importance of identifying at-risk individuals so that effective interventions can be developed to reduce or prevent the adverse consequences of wandering.