Access to this full-text is provided by MDPI.
Content available from Sustainability
This content is subject to copyright.
Citation: Al-Sharaa, A.; Adam, M.;
Amer Nordin, A.S.; Mundher, R.;
Alhasan, A. Assessment of
Wayfinding Performance in Complex
Healthcare Facilities: A Conceptual
Framework. Sustainability 2022,14,
16581. https://doi.org/10.3390/
su142416581
Academic Editors: Hao Wu,
Lingbo Liu and Yang Yu
Received: 11 November 2022
Accepted: 9 December 2022
Published: 10 December 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sustainability
Review
Assessment of Wayfinding Performance in Complex Healthcare
Facilities: A Conceptual Framework
Ammar Al-Sharaa 1, *, Mastura Adam 1, *, Amer Siddiq Amer Nordin 2,3 , Riyadh Mundher 4
and Ameer Alhasan 5
1Department of Architecture, Faculty of Built Environment, University of Malaya,
Kuala Lumpur 50603, Malaysia
2Centre on Addiction Sciences (UMCAS), University of Malaya, Kuala Lumpur 50603, Malaysia
3Department of Psychological Medicine, Faculty of Medicine, University of Malaya,
Kuala Lumpur 50603, Malaysia
4Department of Landscape Architecture, Faculty of Design and Architecture, Universiti Putra Malaysia,
Serdang 43400, Malaysia
5Department of Computer Techniques Engineering, Dijlah University College, Baghdad 00964, Iraq
*Correspondence: ammoratawama@gmail.com (A.A.-S.); mastura@um.edu.my (M.A.)
Abstract:
Wayfinding is considered to be one of the most demanding challenges to be performed by
hospitals’ users. Wayfinding has been an interest among researchers from different fields, such as
architecture, interior design, cognitive psychology, and facilities management, to name a few. Previous
scholars have highlighted the need for a holistic framework taking into consideration both user and
environmental factors. A narrative review of the literature was carried out to understand the full
extent of the issue and address the ever-increasing demand for a holistic assessment framework. This
article attempts to address the underlying gap by proposing a comprehensive framework that takes
into account both facets of the issue through a narrative review of the literature to some of the most
prominent research attempts to address the problem of wayfinding in complex healthcare settings.
Furthermore, the proposed framework can assist both researchers and practicing professionals by
providing a comprehensive understanding of the issue of complex wayfinding as well as of the
variables to be investigated in the assessment process.
Keywords:
wayfinding; pathfinding; navigation; indoor environment; interior environment; healthcare
facilities; hospitals; assessment framework
1. Introduction
Lynch [
1
] was the first to name wayfinding as a potential problem and formally defined
it in his book The Image of the City. Lynch [
1
] recognized wayfinding as a coordinated usage
and delineation of sensory environmental signals. This definition led De Jesus [
2
] to deduce
that wayfinding is, in its essence, a matter of spatial orientation. This concept has been
evolving: wayfinding was then regarded as the process of navigating a space with an
aim to reach a specific destination [
3
]; at the present time, a widely accepted and more
specific definition of wayfinding can be put together as the process in which a person
identifies his current relative spatial location and the knowledge of how he can move
through the space towards the desired destination as quickly and efficiently as possible [
4
].
However, the way in which wayfinding can be defined is highly dependent upon the
field in which an investigation is carried out and the setting from which the definition
is derived [
5
]. Yet, different definitions of wayfinding have a commonality of elements,
based upon which wayfinding can be described as a destination guided motion [
6
]. The
union of spatial and environmental cognition mentioned by Jamshidi and Pati [
7
] is the
reason why people can conduct a thread of decisions incorporating their cognitive abilities
to navigate through both the built and the natural environments. The usage of external
Sustainability 2022,14, 16581. https://doi.org/10.3390/su142416581 https://www.mdpi.com/journal/sustainability
Sustainability 2022,14, 16581 2 of 20
environmental communication means such as maps, signs, or geographic positioning
system-based navigation systems (GPS), or the lack thereof, does not undermine the
reductive definition [8].
The indoor environments of hospitals are some of the most complex environments
to navigate due mainly to the high degree of intersection between functions and activities
and the variety of functional goals and environmental concerns [
9
]. Consequently, the
higher levels of functional integration have led to the spaces being arrayed in specific
patterns to ensure that the required levels of functionality are achieved [10]. According to
Ulrich et al. [
11
], interiors of healthcare facilities have been designed with assertiveness
in order to achieve functional objectives. This practice-oriented tendency may create
an environment that dismisses the psychological needs of patients, visitors, and staff
members [
12
]. Ulrich et al. [
10
] regarded the interior environment of these healthcare
facilities as psychologically challenging and stressful to users. In this regard, the emphasis
on the role of wayfinding and its effects on patients’ physical and psychological states are
apparent. Furthermore, healthcare buildings are not static; new linkages are often built
to connect newly built annexes to the main building [
13
]. These buildings should thus be
viewed as dynamic entities that grow, shift space within their morphology, and change or
alter their topology.
What makes wayfinding especially challenging in healthcare settings compared with
other structures such as airports and shopping centers is that the wayfinding process in
a healthcare setting is highly purposeful at its core. Therefore, it is considered a highly
resolute type of wayfinding [
14
], while wayfinding in airports, shopping centers, and
public parks are regarded as a recreational type of wayfinding [
15
]. Public perceptions
of the role of wayfinding in the promotion of recreational walking routes in greenspace
have been investigated whereby cross-sectional surveys reveal that urgency levels differ
depending on the Space, and Society. Furthermore, hospital patients are considered users
who are cognitively operating at a sub-optimal level, which requires them to pay further
attention to the nuances of wayfinding.
Given the importance of wayfinding performance to both users and healthcare institu-
tions, there have been a paucity of research initiatives attempting to formalize a conceptual
framework for assessing indoor wayfinding performance in complex healthcare facili-
ties that could act as a theoretical guide for future assessment initiatives. Hence, this
study’s main aim is to develop a conceptual framework for the assessment of wayfinding
performance in healthcare facilities.
2. Materials and Methods
This study incorporates a set of keywords to investigate wayfinding in complex health-
care settings. The set of keywords (“wayfinding” OR “way-finding” OR “pathfinding” OR
“navigation” AND “hospital” OR “clinic” OR “healthcare” AND “interior environment”
OR “spatial layout” OR “interior design” OR “interior architecture”) was used to collect
the available research on wayfinding in healthcare facilities and its implications on human
wayfinding performance. Two search engines were utilized to acquire the research articles:
the first was Scopus, while the second was four data bases of EBSCOhost, namely Academic
Search Elite, Art & Architecture Complete, E-Journals, and Psychology and Behavioral
Sciences Collection.
The inclusion criteria implemented by the authors was for the studies to be quantita-
tive, qualitative, or a mixture of both approaches; the studies had to be written in English
with a focus on wayfinding performance. Furthermore, only research articles published
between 2017 and 2022 were included in the search for relevant articles. Moreover, only
articles with available full text and references were included. Research articles were then
screened for relevance on two stages, the first stage being the review of the articles’ titles
and abstract sections and the second being a review of the articles’ full content. The screen-
ing was to eliminate search results findings that were irrelevant. Additional resources
were also included afterwards by employing a snowball technique. Articles were then
Sustainability 2022,14, 16581 3 of 20
analyzed and thematically grouped. A conceptual framework of wayfinding assessment
was then proposed to sum up the theoretical connections explaining the mechanism that
effects the process of wayfinding, the factors/variables included, and the approaches incor-
porated. See Figure 1for further information on the methodology used to collect and sort
the research articles.
Sustainability 2022, 14, 16581 3 of 21
analyzed and thematically grouped. A conceptual framework of wayfinding assessment
was then proposed to sum up the theoretical connections explaining the mechanism that
effects the process of wayfinding, the factors/variables included, and the approaches in-
corporated. See Figure 1 for further information on the methodology used to collect and
sort the research articles.
Figure 1. resources collection methodology.
3. Results
The initial search results indicated a total of 925 related articles. The first screenings
reduced the number of relevant articles to 139; at this stage a total of 27 duplicates were
recognized and removed, resulting in a total number of 112 relevant articles. A second
screening further reduced the number of total relevant articles to 82. An additional total
of 39 research articles were then incorporated through the adapted snowball technique,
resulting in a total of 121 articles.
Four thematically linked research domains resembling the domains of the social eco-
logical model (SEM) were recognized in the research articles found within the papers.
These domains are listed as per the following: The domain of the physical built environ-
ment, the institutional domain, the domain of human cognition, and the social domain.
The upcoming sub-sections of this article discuss the most prominent research attempts
in each domain that were found to be relevant.
Figure 1. Resources collection methodology.
3. Results
The initial search results indicated a total of 925 related articles. The first screenings
reduced the number of relevant articles to 139; at this stage a total of 27 duplicates were
recognized and removed, resulting in a total number of 112 relevant articles. A second
screening further reduced the number of total relevant articles to 82. An additional total
of 39 research articles were then incorporated through the adapted snowball technique,
resulting in a total of 121 articles.
Four thematically linked research domains resembling the domains of the social
ecological model (SEM) were recognized in the research articles found within the papers.
These domains are listed as per the following: The domain of the physical built environment,
the institutional domain, the domain of human cognition, and the social domain. The
upcoming sub-sections of this article discuss the most prominent research attempts in each
domain that were found to be relevant.
4. Assessment of Wayfinding Performance in Healthcare Facilities Based on the (SEM)
Model for Human Environment Interaction
The social ecological theory involves four stages of influences in the interaction of peo-
ple and the environment: individual, social, physical, and policy [
16
]. SEM aimed to further
the understanding of the factors related to people’s encounters with the environment by
mediating between two polarities: people as the focus of research at the micro level, and the
Sustainability 2022,14, 16581 4 of 20
environment as the focus of research on the macro level. An examination of the interaction
of people with a larger environmental context is critical, whereby each level of interaction is
complex and may have a consequence for people’s experience within the environment, with
a tendency to produce a ripple effect through the other layers [
17
]. The social-ecological
model’s holistic approach made it a popular choice for investigating the way humans
interact with the environment; as a result, the integration of multiple factors that affect
the human-environment interaction has become widely accepted. Table 1summarizes the
parameters of the study within the (SEM) framework, and the corresponding factors that
may affect people’s experiences concerning their engagement with the environment.
Table 1. Influencing factors at different domains of the environment.
Social-Ecological Model
Domain Reference Highlights Variables
The individual domain
[18]
Wayfinding induced stress and was correlated with age
•Demographics
•Knowledge of the environment
•Mental representation of the
environment
•Prior experience
[19]Working memory has an effect on wayfinding
performance
[20] Cognitive map and wayfinding
[21] Spatial representation/cognitive mapping
[22] Spatial learning and wayfinding
[23] Cognitive workload effect on wayfinding
[24] Effect of age and fear of confinement on wayfinding
The social domain
[22] Asynchronous wayfinding in complex environments •Attitude of people around other
people (other users and staff
members)
•Type of communication
(synchronous, asynchronous, etc.)
•Availability of information
•Clarity of provided information
[25]Dyad navigation and wayfinding/information
synchronicity and wayfinding
[26]Geo-crowdsourcing services and collecting
accessibility information on the built environment
[27]
Social role-taking (leading and following) within dyads
The physical environment
domain
[9]Physical properties of hospitals’ circulation areas and
wayfinding performance
•Location
•Orientation
•Spatial organization
•Legibility
•Contrast
[28] Physical differentiation effect on wayfinding
[29] Interior spatial quality effects on wayfinding
[30] Physical design elements contributing to wayfinding
[31] Information display effects on wayfinding
[32] Information display effects on wayfinding behavior
[33]
Interior organization and layout effects on wayfinding
patterns
[34]Physical environmental element effects on patients’
satisfaction
[35]Effects of architectural features on enhancing
wayfinding performance
The institutional domain
[34]Interior design quality evaluation in public inpatient
units
•The way-showing devices’
properties/Design (i.e., size, color,
language, etc.)
•Institutional attitude.
[36]Hospital design guidelines and their potential effects
on user satisfaction
[37]
Institutional wayfinding in complex environments and
potential effects on users
[38]Organizational outcomes resulting from controlling
design variables
4.1. Models of Wayfinding as a Function of Human Cognition
The association of both environmental and spatial cognition in enabling people’s
decision making by empowering their cognitive abilities to navigate through the built
or natural environment has been widely recognized [
7
]. However, the occurrence of
Sustainability 2022,14, 16581 5 of 20
wayfinding cognitive processes is not strictly subject to the use of external representations
of the environment such as maps, signs, or GPS systems [
39
]. This implies that wayfinding
is a cognitive process in its essence, which may be the reason why the process is complex
by nature even though it may seem like a simple process [40].
Wayfinding can be understood as a combination of three interlinked processes: first is
the decision-making process, whereby an action plan is developed; it is followed by the
process of decision execution, whereby the action plan will be translated into a set of coor-
dinated behaviors; and lastly information processing, which includes the environmental
perception and cognition sub-processes that are responsible for the basis of information of
the two decision-related processes [7].
Modern empirical research found in the literature has proposed that the process
of wayfinding comprises a set of different cognitive processes such as problem solving,
decision making, decision execution, and behaviors [
21
]. A list of theoretical propositions
that helped in coining our understanding of those cognitive functions is given in the next
upcoming sub-sections, see Table 2.
Table 2. Cognitive factors and effects on hospitals’ wayfinding performance.
Factor Classification References Remarks
Demographic factors
[18]•Wayfinding-induced stress and its correlation with the age of
wayfarers
[19]•Working memory has an effect on wayfinding performance
[41]•Effect of age and fear of confinement on wayfinding
[42]
•Gender effects on wayfinding performance
[43]
[44]
[37]•Level of education effects on wayfinding performance
•Native language effects on wayfinding performance
Spatial knowledge
[22]•Spatial learning association with wayfinding performance
[23]•Cognitive workload effect on wayfinding
[45]•Familiarity effects on wayfinding performance
Mental representation of the
environment
[20]•Cognitive map and wayfinding
[21]•The association of spatial representation/cognitive mapping on
wayfinding performance
4.1.1. Spatial Perception
Theories of Human spatial perception can be described as a group of theories of
perception that attempted to explain the mechanisms in which the perception of sensory in-
formation occurs; these theories also touched on the mechanisms involved in the processes
of information acquisition [
21
]. Falling under this category of theories are Gestalt theory,
the theory of direct perception, template theory, and constructivist theory [
7
]. Gestalt
psychology proposed a set of principles that depict the perception mechanisms of elements
by grouping them (Lu and Pesarakli [
46
]), namely figure-ground, proximity, similarity,
continuity, closure, and symmetry. The theory of direct perception argues that our percep-
tual system can make use of contextual information [
47
]. It has been described as a theory
that relies on data-driven cognitive processing, indicating that information perceived by
Sustainability 2022,14, 16581 6 of 20
our sensory input is satisfactory for perception; it interprets our perception and decision-
making by a simple input-processing-output scheme. According to the theory of direct
perception, there are no “higher-level” cognitive processes required. This indicates that the
environmental cues are satisfactory for environmental perception, which means that our
prior knowledge does not account for much of our environmental perception. It was mostly
referred to in cases where the role of visual information in navigation was investigated [
4
].
Perceptual cycle theory emphasized the importance of retrieving information; accord-
ing to this theory, one collects targeted information from the environment based on the
person’s prior experiences, then the newly collected information is stored and retrieved,
affecting the next cycle of information collection. According to perceptual cycle theory,
a person is attempting to coordinate sensory information with a mental template called
“schemata” in order to discern patterns in the environment [
48
]. In this approach to un-
derstanding wayfinding, one is constructing concepts; hence, it has been labeled as the
constructivist theory [49].
4.1.2. Development of Spatial Knowledge
There has been a class of theoretical propositions attempting to explain the stages
in which spatial knowledge is developed. Two theories are considered the standouts in
this regard, namely Piaget’s theory, which investigated spatial development processes
in children [
50
], and the theory of spatial knowledge acquisition by Siegel and White,
which builds upon Piaget’s theory to examine the same processes among adults especially
in an unfamiliar environment [
51
]. Piaget’s theory was mainly concerned with spatial
knowledge as a means to understand the mechanisms in which this ability develops
during one’s lifetime. This theory states that humans possess progressive levels of spatial
cognitive abilities. Subsequently, the theory of spatial knowledge acquisition suggested
a more general model explaining the mechanisms of acquiring spatial knowledge that
applies to subjects of all ages. The theory suggests that the progression of environmental
knowledge development in adults experiencing an environment for the first time is like
that of children [52].
4.1.3. Mental Representation of Spatial Knowledge
The two important concepts in the theoretical propositions that addressed the mental
representation of spatial knowledge are cognitive map and cognitive mapping. These
theoretical models help to understand how the human mind represents spatial informa-
tion [
53
]. Several studies attempted to simulate formation and the representation of the
cognitive map by using the Component Process Model (CPM) and the Neural Network
Model (NNM) [
54
]. The concept of cognitive maps argued people’s reliance on cognitive
maps to navigate through the environment [
55
]. Cognitive maps are mental representations
of the environment whereby Euclidean information, spatial layouts, and affordances of the
environment can be cognitively portrayed [
56
]. Several studies have investigated people’s
behavior in large-scale environments and have argued that wayfinding behavior can be bet-
ter explained by investigating cognitive maps [
47
]. Lynch [
1
] identified five environmental
factors that people acquire to compose a cognitive image: paths, edges, districts, nodes, and
landmarks. The concept of Cognitive mapping made use of the “neural network” concept
as an analogy to explain the process of cognitive mapping [
57
]. The cognitive mapping
theoretical proposition states that more mental associations are formed between certain
locations as one’s experience increases within an environment [
58
]. Numerous mental
associations may exist which can be interpreted as a network of associations; the network
grows as the person’s experience increases in an environment, which in its turn adds up to
the spatial knowledge of the person [59].
Cognitive mapping is defined generally as the process of acquiring information from
the environment and categorizing it mentally according to its relevance [
60
]. Jamshidi and
Pati [
7
] distinguished two general approaches in cognitive mapping, the first being the neu-
ral network model (NNM) Chang and Leung [
61
], and the second being connectome-based
Sustainability 2022,14, 16581 7 of 20
predictive modelling (CPM) [
62
]. The CPM model is primarily based upon the Information
Processing Theory (IPT) [
63
] in which the human cognitive system is considered as a com-
putation unit. According to the CPM model, spatial information is considered a cognitive
input, then human cognition will inspire changes to the information in accordance with a
pre-determined set of rules, after which the spatial learning process will subsequently occur.
4.1.4. Spatial Cognition
A set of attempts focused on explaining the process of active wayfinding based on an
input such as spatial data to an output such as actions [
64
]. Two main theoretical structures
have emerged under this category, the Information Processing Theory (IPT) and theories
of problem-solving [
65
]. According to IPT there are similarities between the way human
beings register information and the way computers receive data input [
66
]. The theory
goes beyond, viewing the act of thinking as analogous to a computer program, and human
memory or the capacity to store information as analogous to the amount of information
stored on a computing device that can be measured by bits of information. Furthermore, the
theory considers forgetting some information to be similar to the process of actively deleting
information from a computing device, and the process of recalling previously registered
information as a similar process in principle to using an information search function. The
theory also compares strategizing to using computer scheduling tools, and finally the
process of decision making to computer output [
66
]. Information processing scholars
consider the structure of human cognition comparable to the architecture of computers, and
often refer to it as cognitive architecture [
67
]. Theorists in this subject communicated their
findings which illustrated the information flow by utilizing representations of the human
brain as an information processing apparatus [
68
]. Many have expressed the information
flow by illustrating the steps of the flow in the form of flow diagrams, often referred to as
models [
69
]. See Figure 2for a diagram illustrating the information processing mechanisms
that interpret the cognitive information processing as a multi-level processing system.
Sustainability 2022, 14, 16581 8 of 21
Figure 2. Multi-level model of information processing [69].
A model called Test-Operate-Test-Exit (TOTE) attempted to explain information pro-
cessing involved in the process of problem-solving, which is described as incorporating a
feedback loop procedure in order to solve problems [70]. In this model, one examines the
achievement of goals, and in cases where goals have not been achieved a reaction in ac-
cordance with the feedback is occurring, upon which examination starts again [71]. This
cyclical process continues until objectives are met. Similarly, a successful wayfinding pro-
cedure is based on a continuous examination and feedback processes [72]. The examina-
tion procedure can be seen in wayfinding-related problem-solving strategies such as the
process of rout Control, in which wayfinding action continues if no alternative route is
deemed more affordable [21].
4.1.5. The Evolutionary Theoretical Proposition for Spatial Sex Differences
The hunter gatherer theory is a theory highlighting spatial differences between sexes.
These differences were attributed to various empirical evidence showing differences in
the performance of spatial tasks between genders [73]. Several research articles argued
that an evolutionary theory can explain the root of these differences [7]. The argument of
an evolutionary origin was developed based on the fact that males were engaged in hunt-
ing activities more frequently than their female counterparts; on the other hand, females
were engaged more in foraging. This led to the variation in spatial development and ca-
pabilities which were more suitable for the tasks that they were engaged in. Accordingly,
males needed to develop abilities such as mental rotation, which is essential to successful
hunting. The development of mental rotation can facilitate map reading and maze learn-
ing [42]. Hence, males outperform females in these kinds of spatial tasks [74]. On the other
hand, successful foraging needed the ability to memorize objects and their location for
further inspections [75]. That explains the superiority of females in recalling objects and
their locations compared to males in several studies [43]. Moreover, several empirical
studies suggest that spatial abilities such as mental rotation and sense of direction play an
important role in explaining gender differences in wayfinding [76]. Therefore, the hunter-
gatherer theory attempts to explain the reason spatial sex differences exist.
4.2. The Social Domain in Wayfinding
Figure 2. Multi-level model of information processing [69].
A model called Test-Operate-Test-Exit (TOTE) attempted to explain information pro-
cessing involved in the process of problem-solving, which is described as incorporating
Sustainability 2022,14, 16581 8 of 20
a feedback loop procedure in order to solve problems [
70
]. In this model, one examines
the achievement of goals, and in cases where goals have not been achieved a reaction in
accordance with the feedback is occurring, upon which examination starts again [
71
]. This
cyclical process continues until objectives are met. Similarly, a successful wayfinding proce-
dure is based on a continuous examination and feedback processes [
72
]. The examination
procedure can be seen in wayfinding-related problem-solving strategies such as the process
of rout Control, in which wayfinding action continues if no alternative route is deemed
more affordable [21].
4.1.5. The Evolutionary Theoretical Proposition for Spatial Sex Differences
The hunter gatherer theory is a theory highlighting spatial differences between sexes.
These differences were attributed to various empirical evidence showing differences in the
performance of spatial tasks between genders [
73
]. Several research articles argued that
an evolutionary theory can explain the root of these differences [
7
]. The argument of an
evolutionary origin was developed based on the fact that males were engaged in hunting
activities more frequently than their female counterparts; on the other hand, females were
engaged more in foraging. This led to the variation in spatial development and capabilities
which were more suitable for the tasks that they were engaged in. Accordingly, males
needed to develop abilities such as mental rotation, which is essential to successful hunting.
The development of mental rotation can facilitate map reading and maze learning [
42
].
Hence, males outperform females in these kinds of spatial tasks [
74
]. On the other hand,
successful foraging needed the ability to memorize objects and their location for further
inspections [
75
]. That explains the superiority of females in recalling objects and their
locations compared to males in several studies [
43
]. Moreover, several empirical studies
suggest that spatial abilities such as mental rotation and sense of direction play an important
role in explaining gender differences in wayfinding [
76
]. Therefore, the hunter-gatherer
theory attempts to explain the reason spatial sex differences exist.
4.2. The Social Domain in Wayfinding
Despite the numerous studies investigating wayfinding as a primary or a secondary
objective, there has been a paucity of research focused on studying wayfinding as a social
activity as it has been treated mostly as an issue facing individuals. Similarly, studies
of agent-based modeling, in which pedestrian agents are created to simulate pedestrian
movements, treated pedestrian movement as movements of single units without any
interaction with other simulated agents or groups [
77
,
78
]. Further research on the social
aspects of wayfinding is in the field of research of verbal communication in wayfinding
instructions, which focuses on communicating route directions [
79
]. Dalton et al. [
25
]
indicated that examining instructions in wayfinding involves studying social wayfinding
implicitly due to the involvement of multiple individuals, while mostly focusing on the
content of the information supplied in the instructions such as word count, instructions
platform, and landmarks. Some research attempts focused on either dyad navigation or the
effects of the presence and behavior of other navigators on one’s wayfinding performance
and behavior [
27
,
80
]. This suggests that wayfinding instructions in both forms, direct and
indirect, are a type of social wayfinding.
Forlizzi et al. [
81
] noted the interaction between traveling pairs when using vehicular
navigation systems, which yielded a set of findings regarding the design of navigation
systems. Another study conducted by Haddington [
82
] focused on gestures and conversa-
tional exchanges among people regarding vehicular navigation. Similarly, He et al. [
83
]
examined pairs of individuals’ walking route choices in an unfamiliar urban environment.
These research initiatives focused on observing social interactions occurring among co-
navigators in a particular setting. Dalton et al. [
25
] hypothesized that social wayfinding can
be investigated further beyond simply co-navigating pairs (or, as researchers describe them,
“dyads”) and beyond simple synchronous interaction between co-navigating members.
Sustainability 2022,14, 16581 9 of 20
An interesting study of possible social interactions among multiple wayfinding people
was conducted by Haghani and Sarvi [
84
], who examined the effect that social behaviors
have while performing a simulated emergency evacuation. The study’s results suggested
that peoples’ emergency exit strategies are heavily affected by both the physical environ-
mental factors and social interactions. However, this paper’s sole focus was investigating
people’s wayfinding behavior in an emergency event, and it therefore may not be predictive
about other wayfinding tasks.
Bae [
85
] indicated that problem-solving and reasoning is primarily a socio-cultural
process, found in the communication of groups of individuals and artifacts generated
by previous group members. Hutchins [
86
] also found that group cognition could vary
from the cognition of the agents taking part in performing the task within the group and is
different from the total sum of the contributions made by the individuals forming the group.
4.2.1. Types of Social Wayfinding
Dalton et al. [
25
] proposed a classification of social wayfinding into two types, Strong
and Weak social wayfinding. Strong and Weak social wayfinding were defined according
to the embedded “degree of intentionality” in the process of exchanging information. In
the case of Strong social wayfinding, it was defined as an intentional exchange of infor-
mation about the wayfinding process between “co-navigators”, where more than a single
individual exchanges information regarding the location or the route choice. Alternatively,
Weak social wayfinding was defined by the unintentional communication between the
actors which means that there is no occurring co-navigation. Weak social wayfinding takes
place when individuals unintentionally communicate information regarding the location
or the choice of rout. In this type of social wayfinding, cues are generally created by the
individual without the intention of providing them, as a by-product of their own navigation.
Strong social wayfinding generally involves direct communication between senders and
recipients, most often between individuals in proximity. On the contrary, Weak social
wayfinding often occurs remotely, within the extent of sensory access. Wayfinding was also
classified, according to the timeframe of the information exchange, into synchronous and
asynchronous. Therefore, each of the types can be divided according to the synchronicity of
communication among individuals, resulting in a total of four types of social wayfinding,
see Table 3.
Synchronous Social Wayfinding
Synchronous social wayfinding takes place when an influence from others occurs
during the navigation process. In this case, one makes their decisions with accordance
to an intentionally generated external input. The contribution of an external information
source is direct and intentional. When conducted by another co-navigator within proximity,
by incorporating verbal and/or gestural communication, it is called Strong synchronous
wayfinding. When others navigate alongside each other, it is safe to assume prior knowl-
edge amongst these people. However, information inquiry and exchange can be a form
of social interaction among people. In contrast to Strong social wayfinding, other people
can influence wayfinding decision-making in indirect and unintentional ways, which is
referred to as Weak social wayfinding. When this Weak influence expresses itself during
the actual travel of a navigating person, it is not only Weak but also Synchronous. This
type of wayfinding can be best represented in studies in which participants were finding
their destinations within a space by incorporating verbal communication as a means of
communication [88–90] or by mimicking other people’s wayfinding behavior [41,87].
Asynchronous Social Wayfinding
According to Dalton et al. [
25
], social wayfinding can take place without synchronicity.
In these cases, information exchange regarding wayfinding decisions takes place at a time
prior to the travel in the form of given instructions. These instructions can take various
forms, such as written, spoken, or gestured. Another form of achieving asynchronous
Sustainability 2022,14, 16581 10 of 20
social wayfinding can take place by the usage of maps, which are a more common mode of
instruction delivery in asynchronous wayfinding than they are in synchronous wayfinding.
It is worth noting that in both synchronous and asynchronous wayfinding, supplying
information by a non-traveler is considered a less engaging system than Strong wayfinding.
The process of supplying instructions to other navigators is usually reliant on one person
assisting another without accompanying that second person during the travel.
Table 3. Types of social wayfinding and related studies.
Factor Type References Remarks
Communication
Strong
[22]•
Asynchronous strong wayfinding in complex environments
[25]•Dyad navigation and wayfinding/information
synchronicity and wayfinding
[27]•Social role-taking (leading and following) within dyads
Weak
[25]•Dyad navigation and wayfinding/information
synchronicity and wayfinding
[26]•Geo-crowdsourcing services and collecting accessibility
information on the built environment
[87]•
Occupants’ behavior in an emergency scenario and the effect
of the crowd
Synchronicity
Synchronous
[88]•Asking people passing by for verbal assistance
[89]•The effect of verbal memory on wayfinding familiarity
[90]•The use of mobile applications in wayfinding to assist the
visually impaired in improving wayfinding and safety
Asynchronous
[91]•The use of social media digital cues as a wayfinding aid
[92]•The use of mobile digital technology as a navigation aid
4.3. Wayfinding and the Physical Built Environment
Wayfinding can be considered an important aspect of environmental spatial quality.
Colenberg et al. [
93
] defined the spatial quality of environmental interiors by the structure
and enclosures formed by the architectural elements which comprise the environment,
such as floors, ceilings, walls, windows, and vertical movement bridging elements such as
stairwells and elevators. Interior elements of the environment can serve both visual and
functional purposes by incorporating elements such as materials’ properties, construction
elements’ properties, and technology. Visible elements of interior environments conform
interior spaces into a habitable and functional space. Similarly, the American Society of
Interior Design (ASID) (2008) [
94
] considers interior design, in its core, a functional process
that can enhance living quality as well as being culturally influential. The (2008) published
interior design manual goes further in detailing dimensions of interior design quality
including outcomes of productivity, health, safety, and wellbeing of the users. According to
a study conducted by Abu Samah [
29
], components of spatial quality in healthcare settings
can be broken down to its principal components, namely technical, functional, and aesthetic.
It is worth noting that there was an overlap between components of spatial quality and
components that were investigated in the context of wayfinding studies, see Table 4. The
next three subsections list the elements that have been mentioned in the literature whose
effect on wayfinding performance was measured directly or indirectly.
Sustainability 2022,14, 16581 11 of 20
Table 4.
Literature on the components of the interior environment that were found to be affecting
wayfinding performance in hospital buildings through affecting perceived spatial quality.
Component(s)
Classification Factors/Variables References Remarks
Technical 1. Safety
2. Lighting
[95]•Appropriate lighting promoted indoor
wayfinding
[96]
•People feel safer in a uniformly lit
environment
•
Separated light zones enhance wayfinding, as
they can be read together as a coherent
pattern
[97]•Color temperature does have a significant
effect on hesitation
[98]•Lighting’s effects on perceived safety
Functional 1. Accessibility/permeability
2. Spatial layout
3. Information display
[23]•Information formatting’s effects on
wayfinding performance
[74]•The effects of map design on wayfinding
performance
[99]•Users’ permeability in two different
typologies
[100]•
Spatial layout’s effects on wayfinding and the
level of social contact amongst individuals
[101]•Spatial layout complexity and similarity
effects wayfinding performance
[102]•Spatial layout typology and wayfinding
performance
Aesthetic 1. Colors
2. Materials and textures
[103]
•Color helps in spatial identification
•Color conspicuity and information
comprehensibility are hard to consolidate
simultaneously
[104]•The texture of the environment’s finishing
materials can affect navigators’ safety
4.3.1. Technical Components’ Effect on Wayfinding Performance
Abu Samah [
29
] classified lighting, thermal comfort, air quality, noise, and safety as
technical components. Two elements, air quality and thermal comfort, have no obvious
direct effect on the process of wayfinding. Meanwhile it is widely agreed upon that
wayfinding and other ergonomic interior design elements might reduce the number of
falling staff members and the number of injuries occurring, and could also reduce potential
violent actions [
105
]. Alternatively, two other technical elements, light and noise, have been
discussed by the studies concerning wayfinding and indoor navigation extensively and are
considered to have a direct significant effect on wayfinding performance. Studies showed
that subjects are more likely to have a bias towards the brighter lit paths as opposed
to the darker ones. Higher noise level is shown to have a potential negative effect on
certain patient outcomes [
106
,
107
]. There is also some evidence that staff personnel might
experience higher stress levels caused by higher sound levels in patient units [108].
Sustainability 2022,14, 16581 12 of 20
4.3.2. Functional Components’ Effect on Wayfinding Performance
Wayfinding was discussed as a functional aspect of the hospital’s design that con-
tributes to its perceived spatial quality. Functional aspects of spatial quality were divided
into spatial planning, accessibility, wayfinding, and furniture. It is our understanding that
accessibility and wayfinding are both characteristics of the spatial layout that vary from one
spatial layout to another, accentuated by an indoor purposefully designed and scattered
items serving as wayfinding cues and features to achieve spatial differentiation, especially
in cases where the interior environment lacks the means in which it could differentiate
its parts from one another without causing confusion and cognitive load. Architectural
wayfinding design was defined by Hunter [
109
] as the function that addresses the built
components, including spatial planning, articulation of form-giving features, circulation
systems, and environmental communication. Good wayfinding systems should go beyond
mere signage and the use of color codes to differentiate various hospital areas; this em-
phasizes the role of a good wayfinding system on both a user level and an organizational
level [
21
]. Spatial layout is directly correlated to all three environmental physical properties,
namely appearance differentiation, visual accessibility, and complexity of the building’s
layout [
110
]. Visual access is the environmental extent that allows human vision to ob-
serve features and objects [
110
], while accessibility is usually correlated to the sequence of
activities. Furthermore, accessibility is related to users’ movement through the building
environment from their origin of movement to their desired destination. Accessibility of
physically disabled users is usually the focus when inclusive design is an objective of the
institution [
111
]. Lighting is another functional aspect of spatial quality showing a direct
effect on wayfinding performance [
34
]. Experimental evidence indicates that users are
more likely to favor a well-illuminated environment when selecting routs. There are two
types of studies that can be found in the published literature: the first is focused on indoor
lighting in hospitals generally and its effects on wayfinding performance [
80
,
95
], while
the second type’s focus is primarily on natural lighting and its potential for psychological
relief [112,113].
4.3.3. Aesthetic Components’ Effect on Wayfinding Performance
Color can affect the way in which direction signage and orientation systems are
perceived, which contributes to aspects of safety, efficiency, wellbeing, and spatial veri-
fication [
114
,
115
]. Multiple research studies have mentioned the importance of color in
creating a pleasant and comfortable feeling towards the environment [
116
,
117
]. Contrasting
colors and intensities may aid in the process of discernment of different spatial elements
for the purpose of definition, separating different areas, showing directions, marking floor
levels, signaling intersections, and indicating destinations. Previous research also indi-
cated that color should be used carefully and recommended that only a limited number
of contrasting colors be used, due to the possibility of users, especially those undergoing
highly stressful circumstances, not distinguishing and memorizing subtle nuances [
103
,
118
].
Materials and finishes of the interior environment also seem to influence wayfinding: liter-
atures suggest an effect on safety, specifically avoiding slippery flooring which can lead to
injuries [104,119].
4.4. Institutional Influences on Wayfinding in Healthcare Facilities
Empirical studies indicated that complex medical facilities with excessive institutional
environments have triggered several undesirable outcomes for their users, with wayfinding
being one of them [
5
,
37
]. Other research focused on identifying these adverse outcomes,
such as the study conducted by Jiang and Verderber [
9
], which highlighted the potential
resulting outcomes of these environments commonly described as challenging, among
which causes of high levels of stress and anxiety, loss of perceived control, and insufficient
accessibility to positive distractions were described as the lack of meaningful interaction
with nature. A number of published research articles mentioned the institutional role in
wayfinding at healthcare facilities [
29
,
34
]. An example of how institutional nuance can
Sustainability 2022,14, 16581 13 of 20
make a slight difference due to difference in priorities was the example of teaching hospitals,
which are under the institutional jurisdiction and management of the Ministry of Education
(MoE) [
5
,
36
]. Teaching hospitals serve their role as constituents of a Healthcare System with
a slightly nuanced set of priorities geared towards learning and teaching. On the contrary,
privately owned and operated healthcare facilities are not fully integrated with the national
healthcare system and operate under their own accordance, while following the rules and
regulations set by their respective governing bodies [
120
,
121
]. This indicates that healthcare
facilities are mandated by the regulations of their own respective governing bodies.
Institutions do have some level of room to innovate and nuance themselves to stand
out from the competition. These institutional decisions can potentially affect the experience
of patients and families as well as other institutional outcomes [
122
,
123
]. Wayfinding re-
searches in highly institutionalized environments have been conducted in multiple settings
such as libraries [
124
], university campuses [
37
], airport terminals [
125
], train stations
(112), and hospitals [
126
]. These studies assume that the spatial layout is designed in a
pre-construction phase and carried out to operation as designers intended, and that once
facilities are set to a location they remain there. However, upgrading facilities and changes
in recommended practices are frequent enough to consider spatial reassignment every
now and then, which in its turn can influence wayfinding via affecting the environment.
Institutions, in most cases, like to be involved in the processes of decision making especially
when the decisions may lead to institutional outcomes such as the outcomes mentioned by
Ulrich et al. [
38
], who highlighted a set of thirteen potential institutional outcomes resulting
from the implementation of evidence-based design (EBD) practices. Wayfinding problems
can be addressed effectively by integrating improvements to the physical environment
with organizational and operational changes [127].
5. Wayfinding Assessment Approaches
Wayfinding assessment approaches can be sorted into three categories based on
their approach (See Figure 3). Studies concerned with human cognitive abilities, and the
variations in wayfinding capabilities among different demographic groups, were in general
focused on how a physical or cognitive impairment can affect the overall performance and
how these effects can be mitigated; these studies showed promising suggestions for how
the hospital’s interior environment can play a crucial role in achieving inclusivity.
Sustainability 2022, 14, 16581 14 of 21
dementia and Alzheimer’s on wayfinding performance in healthcare facilities [9]. Moreo-
ver, there has been an interest in the physical environment as the basis in which the lived
or perceived space was cognitively formed; therefore, the focus was steered towards the
physical elements of the environment. In a comprehensive multi-method non-experi-
mental, qualitative, exploratory design study, Pati et al. [30] found that physical design
elements contributing to wayfinding include signs, architectural features, maps, interior
elements (artwork, display boards, information counters, etc.), functional clusters, interior
elements pairing, structural elements, and furniture.
Conversely, an emergent pattern in recent studies was to try to establish a quantita-
tive approach to assessing wayfinding performance while still encompassing user experi-
ences as a factor. The usage of visual reality models [30] and eye tracking [46] offer a more
transferable wayfinding assessment data that were not possible without the usage of mod-
ern-day technologies. The use of these emerging technologies has enabled recent re-
searches to bridge the gap between studies focusing solely on the user experience or on
the physical environment [24,42].
Furthermore, studies such as Vizzari et al. and Khasraghi [77,78] were focused on
developing methods of quantizing human spatial behavior based on visual input. In ad-
dition, a set of spatial measures that are either visual, such as Isovist measurands [115], or
topological, such as spatial syntactical measurands [130], were suggested to be a predictor
of wayfinding performance.
Figure 3. Research approaches in the field of wayfinding.
This taxonomy of approaches is consistent with the one proposed by [131,132]; alt-
hough it was not wayfinding-specific, the principles of human-environmental interaction
are similar.
6. Conceptual Framework for the Assessment of Wayfinding Performance in Complex
Healthcare Facilities
The primary investigation of literature led to the realization that wayfinding was in-
vestigated primarily from within one of four domains that represents a set of thematically
linked factors. This study proposes a conceptual framework for wayfinding performance
assessment that considers all four contributing domains of wayfinding: the domain of hu-
man cognition, the domain of the physical built environment, the social domain, and the
institutional domain.
The four aforementioned domains contain a set of variables that have been the pri-
mary target of investigation in the available literature on wayfinding. The proposed
framework highlights the variables that are considered the primary predictors of way-
finding performance in general and in healthcare facilities specifically.
The wayfinding task is governed by both the environmental and the institutional fac-
tors by means of environmental and institutional constraints. The environmental con-
straints are interpreted as the sum of the constraints that are imposed by the environment
on the user when the user starts his wayfinding journey in the environment. The
Figure 3. Research approaches in the field of wayfinding.
En and bin Bebit [
128
] conducted a study focused on analyzing reactions to signage
design within a healthcare facility, whereby a qualitative approach by adopting an in-
terview was suggested as an examination technique. Moreover, a study conducted by
Zijlstra et al. [
129
] focused on simulated physical ageing indicated that rout complexity can
affect aging people negatively when a wayfinding experiment was conducted to simulate
Sustainability 2022,14, 16581 14 of 20
the elderly. Other Studies have focused on the effect of cognitive impairments such as
dementia and Alzheimer’s on wayfinding performance in healthcare facilities [
9
]. More-
over, there has been an interest in the physical environment as the basis in which the lived
or perceived space was cognitively formed; therefore, the focus was steered towards the
physical elements of the environment. In a comprehensive multi-method non-experimental,
qualitative, exploratory design study, Pati et al. [
30
] found that physical design elements
contributing to wayfinding include signs, architectural features, maps, interior elements
(artwork, display boards, information counters, etc.), functional clusters, interior elements
pairing, structural elements, and furniture.
Conversely, an emergent pattern in recent studies was to try to establish a quantitative
approach to assessing wayfinding performance while still encompassing user experiences
as a factor. The usage of visual reality models [
30
] and eye tracking [
46
] offer a more
transferable wayfinding assessment data that were not possible without the usage of
modern-day technologies. The use of these emerging technologies has enabled recent
researches to bridge the gap between studies focusing solely on the user experience or on
the physical environment [24,42].
Furthermore, studies such as Vizzari et al. and Khasraghi [
77
,
78
] were focused on
developing methods of quantizing human spatial behavior based on visual input. In
addition, a set of spatial measures that are either visual, such as Isovist measurands [
115
],
or topological, such as spatial syntactical measurands [
130
], were suggested to be a predictor
of wayfinding performance.
This taxonomy of approaches is consistent with the one proposed by [
131
,
132
]; al-
though it was not wayfinding-specific, the principles of human-environmental interaction
are similar.
6. Conceptual Framework for the Assessment of Wayfinding Performance in Complex
Healthcare Facilities
The primary investigation of literature led to the realization that wayfinding was
investigated primarily from within one of four domains that represents a set of thematically
linked factors. This study proposes a conceptual framework for wayfinding performance
assessment that considers all four contributing domains of wayfinding: the domain of
human cognition, the domain of the physical built environment, the social domain, and the
institutional domain.
The four aforementioned domains contain a set of variables that have been the primary
target of investigation in the available literature on wayfinding. The proposed framework
highlights the variables that are considered the primary predictors of wayfinding perfor-
mance in general and in healthcare facilities specifically.
The wayfinding task is governed by both the environmental and the institutional
factors by means of environmental and institutional constraints. The environmental con-
straints are interpreted as the sum of the constraints that are imposed by the environment on
the user when the user starts his wayfinding journey in the environment. The subsequent
assessment approaches are also highlighted in the proposed framework, as illustrated in
Figure 4.
Sustainability 2022,14, 16581 15 of 20
Sustainability 2022, 14, 16581 15 of 21
subsequent assessment approaches are also highlighted in the proposed framework, as
illustrated in Figure 4.
Figure 4. Conceptual framework for wayfinding performance assessment.
Figure 4. Conceptual framework for wayfinding performance assessment.
7. Limitations and Future Work
Despite its findings, this study has several limitations. Firstly, the study employed a
set of keywords to acquire research articles that are used to formulate the understanding of
terms and mechanisms involved in indoor wayfinding in healthcare facilities; the incorpo-
ration of other keywords might reveal another dimension of wayfinding performance in
healthcare facilities outside of what is discussed in this paper.
Secondly, this study has employed the search results of only two engines, namely
Scopus and EBSCOhost; incorporating research articles from other search engines such as
web of science (WOS) could further enrich the findings of the study and may have offered
a set of articles offering a different perspective from the findings discussed in this research.
Thirdly, this study included research articles published between 2017 and 2022, and
while the snowball technique managed to include some articles out of this timeframe,
conducting a research articles survey that incorporates research articles from a longer
timeframe could offer a perspective on the linear progression of research in wayfinding in
general as well as wayfinding research in healthcare facilities.
Furthermore, this study discusses significant aspects of the assessment of wayfinding
performance in healthcare facilities; however, a quantitative analysis is not included. Fu-
ture research initiatives are encouraged to further investigate the quantitative aspects of
published research studies within the subject matter.
8. Conclusions
Wayfinding in complex healthcare facilities can be a highly taxing process on both
patients and visitors. This challenging process can have multiple physical and psychological
implications which result indirectly in potential institutional adverse outcomes such as
monetary losses, energy waste, and distraction of staff members, as well as potentially
affecting the institution’s image. This manuscript’s main aim is to conduct a review of the
Sustainability 2022,14, 16581 16 of 20
available literature on the assessment of wayfinding performance in healthcare facilities
to then suggest an assessment conceptual framework. This study also provides a generic
wayfinding definition that is based on the theoretical background discussed in this paper.
The manuscript offers a set of potential implications for both theoretical and practical
fronts by presenting a generic definition for wayfinding which can enrich the current
understanding of the wayfinding process, as well as the conceptual assessment framework
which can form the basis for future wayfinding performance assessment initiatives. Future
research initiatives focusing on the assessment of wayfinding performance in complex
healthcare facilities can utilize this conceptual framework in terms of identifying the factors
and variables involved in wayfinding in complex healthcare facilities.
Author Contributions:
Conceptualization, A.A.-S. and M.A.; data review, A.A.-S., A.A. and M.A.;
writing—original draft preparation, A.A.-S. and A.S.A.N.; review and editing, A.A.-S., M.A., A.S.A.N.,
R.M., and A.A.; visualization, R.M. and A.A.; supervision, M.A. and A.S.A.N. All authors have read
and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
References
1. Lynch, K. The Image of the City; MIT Press: Cambridge, MA, USA, 1960; Volume 11, p. 194.
2. De Jesus, S.C. Environmental communication: Design planning for wayfinding. Des. Issues 1994,10, 33–51. [CrossRef]
3.
Casakin, H.; Barkowsky, T.; Klippel, A.; Freksa, C. Schematic maps as wayfinding aids. In Spatial Cognition II; Springer:
Berlin/Heidelberg, Germany, 2000; pp. 54–71.
4.
Brunyé, T.T.; Gardony, A.L.; Holmes, A.; Taylor, H.A. Spatial decision dynamics during wayfinding: Intersections prompt the
decision-making process. Cogn. Res. Princ. Implic. 2018,3, 13. [CrossRef]
5.
Al-Sharaa, A.; Adam, M.; Amer Nordin, A.S.; Alhasan, A.; Mundher, R.A. User-Centered Evaluation of Wayfinding in Outpatient
Units of Public Hospitals in Malaysia: UMMC as a Case Study. Buildings 2022,12, 364. [CrossRef]
6.
Al-Sharaa, A.; Adam, M.; Amer Nordin, A.S.; Alhasan, A.; Mundher, R.; Zaid, O. Enhancing Wayfinding Performance in Existing
Healthcare Facilities Using Vir tual Reality Environments to Revise the Distribution of Way-Showing Devices. Buildings
2022
,12, 790.
[CrossRef]
7.
Jamshidi, S.; Pati, D. A narrative review of theories of wayfinding within the interior environment. HERD Health Environ. Res.
Des. J. 2021,14, 290–303. [CrossRef]
8.
Kuliga, S.; Berwig, M.; Roes, M. Wayfinding in people with Alzheimer’s disease: Perspective taking and architectural cognition—A
vision paper on future dementia care research opportunities. Sustainability 2021,13, 1084. [CrossRef]
9.
Jiang, S.; Verderber, S. On the Planning and Design of Hospital Circulation Zones: A Review of the Evidence-Based Literature.
HERD Health Environ. Res. Des. J. 2017,10, 124–146. [CrossRef]
10.
Ulrich, S.; Grill, E.; Flanagin, V.L. Who gets lost and why: A representative cross-sectional survey on sociodemographic and
vestibular determinants of wayfinding strategies. PLoS ONE 2019,14, e0204781. [CrossRef]
11.
Ulrich, R.S.; Cordoza, M.; Gardiner, S.K.; Manulik, B.J.; Fitzpatrick, P.S.; Hazen, T.M.; Perkins, R.S. ICU patient family stress
recovery during breaks in a hospital garden and indoor environments. HERD Health Environ. Res. Des. J.
2020
,13, 83–102.
[CrossRef]
12.
Deng, L.; Romainoor, N.H. A bibliometric analysis of published literature on healthcare facilities’ wayfinding research from 1974
to 2020. Heliyon 2022,8, e10723. [CrossRef]
13.
Chahal, H.; Gupta, M.; Lonial, S. Operational flexibility in hospitals: Scale development and validation. Int. J. Prod. Res.
2018
,56, 3733–3755.
[CrossRef]
14.
Greenroyd, F.L.; Hayward, R.; Price, A.; Demian, P.; Sharma, S. A tool for signage placement recommendation in hospitals based
on wayfinding metrics. Indoor Built Environ. 2018,27, 925–937. [CrossRef]
15.
Ryan, D.J.; Hill, K.M. Public perceptions on the role of wayfinding in the promotion of recreational walking routes in greenspace–
cross-sectional survey. Wellbeing Space Soc. 2022,3, 100–111. [CrossRef]
16.
Khalilollahi, A.; Kasraian, D.; Kemperman, A.D.; van Wesemael, P. Application of the COM-B model to the correlates of children’s
outdoor playing and the potential role of digital interventions: A systematic literature review. Child. Geogr.
2022
, 1–17. [CrossRef]
Sustainability 2022,14, 16581 17 of 20
17.
Riazi, N.A.; Wunderlich, K.; Yun, L.; Paterson, D.C.; Faulkner, G. Social-Ecological Correlates of Children’s Independent Mobility:
A Systematic Review. Int. J. Environ. Res. Public Health 2022,19, 1604. [CrossRef]
18.
Moore, K.D. Healthy Places: Towards a Transdisciplinary Mapping of the Theoretical Landscape. ARCC J. Archit. Res.
2020
,17, 1–20.
19.
Wang, Y. Comparison and Quantification of Cognitive Load generated by Sternberg Test using EEG Signals. Constr. Res. Congr.
2020,4, 19–31.
20.
Weisberg, S.M.; Newcombe, N.S. Cognitive maps: Some people make them, some people struggle. Curr. Dir. Psychol. Sci.
2018
,
27, 220–226. [CrossRef]
21.
Jamshidi, S.; Ensafi, M.; Pati, D. Wayfinding in interior environments: An integrative review. Front. Psychol.
2020
,11, 549–628.
[CrossRef]
22.
He, Q.; McNamara, T.P.; Bodenheimer, B.; Klippel, A. Acquisition and transfer of spatial knowledge during wayfinding. J. Exp.
Psychol. Learn. Mem. Cogn. 2019,45, 13–64. [CrossRef]
23.
Verghote, A.; Al-Haddad, S.; Goodrum, P.; Van Emelen, S. The effects of information format and spatial cognition on individual
wayfinding performance. Buildings 2019,9, 29. [CrossRef]
24.
Lin, J.; Cao, L.; Li, N. Assessing the influence of repeated exposures and mental stress on human wayfinding performance in
indoor environments using virtual reality technology. Adv. Eng. Inform. 2019,39, 53–61.
25. Dalton, R.C.; Hölscher, C.; Montello, D.R. Wayfinding as a social activity. Front. Psychol. 2019,10, 142. [CrossRef]
26.
Karimi, H.A.; Zhang, L.; Benner, J.G. Personalized accessibility map (PAM): A novel assisted wayfinding approach for people
with disabilities. Ann. GIS 2014,20, 99–108.
27.
Bae, C.J.; Montello, D.R. Dyadic route planning and navigation in collaborative wayfinding. In Proceedings of the 14th
International Conference on Spatial Information Theory (COSIT 2019), Regensburg, Germany, 9–13 September 2019; pp. 1–20.
28.
Ching, F.D.; Binggeli, C. Interior Design Illustrated, 4th ed.; John Wiley & Sons: Hoboken, NJ, USA; University of Washington:
Seattle, WA, USA, 2018; p. 400.
29.
Abu Samah, Z. Physical Assessment of Specialist Clinics in Public Hospitals. Ph.D. Thesis, Universiti Teknologi MARA, Shah
Alam, Malaysia, April 2018.
30.
Pati, D.; Harvey, T.E., Jr.; Willis, D.A.; Pati, S. Identifying elements of the health care environment that contribute to wayfinding.
HERD Health Environ. Res. Des. J. 2015,8, 44–67.
31.
Rodrigues, R.; Coelho, R.; Tavares, J.M.R. Healthcare signage design: A review on recommendations for effective signing systems.
HERD Health Environ. Res. Des. J. 2019,12, 45–65. [CrossRef]
32.
Anuar, N.K.; Pagliari, R.; Moxon, R. An evaluation of airport wayfinding and signage on senior driver behaviour and safety of
airport road access design. J. Air Transp. Stud. 2017,8, 108–129. [CrossRef]
33.
Pouyan, A.E.; Ghanbaran, A.; Shakibamanesh, A. Impact of circulation complexity on hospital wayfinding behavior (Case study:
Milad 1000-bed hospital, Tehran, Iran). J. Build. Eng. 2021,44, 102931. [CrossRef]
34.
Aljunid, S.S.; Shukri, N.N.H.M.; Taib, M.Z.M.; Samah, Z.A. Determinants of patient satisfaction on interior design quality of
public hospitals in malaysia. Malays. J. Public Health Med. 2020,20, 233–241.
35.
Kalantari, S.; Tripathi, V.; Kan, J.; Rounds, J.D.; Mostafavi, A.; Snell, R.; Cruz-Garza, J.G. Evaluating the impacts of color, graphics,
and architectural features on wayfinding in healthcare settings using EEG data and virtual response testing. J. Environ. Psychol.
2022,79, 101744. [CrossRef]
36.
Nawawi, N.M.; Sapian, A.R.; Majid, N.H.A.; Aripin, S. Hospital design in tropical Malaysia towards a green agenda. In
Proceedings of the Annual Healthcare Forum+ Gupha Meeting at IIDEX, Toronto, ON, Canada, 24–28 September 2019; pp. 1–47.
37.
Iftikhar, H.; Asghar, S.; Luximon, Y. The efficacy of campus wayfinding signage: A comparative study from Hong Kong and
Pakistan. Facilities 2020,38, 871–892. [CrossRef]
38.
Ulrich, R.S.; Berry, L.L.; Quan, X.; Parish, J.T. A conceptual framework for the domain of evidence-based design. HERD Health
Environ. Res. Des. J. 2010,4, 95–114. [CrossRef] [PubMed]
39.
Devlin, A.S. Wayfinding in healthcare facilities: Contributions from environmental psychology. Behav. Sci.
2014
,4, 423–436.
[CrossRef]
40.
Farr, A.C.; Kleinschmidt, T.; Yarlagadda, P.; Mengersen, K. Wayfinding: A simple concept, a complex process. Transp. Rev.
2012
,
32, 715–743. [CrossRef]
41.
Lin, B.S.M.; Lin, C.Y.; Kung, C.W.; Lin, Y.J.; Chou, C.C.; Chuang, Y.J.; Hsiao, G.L.K. Wayfinding of firefighters in dark and complex
environments. Int. J. Environ. Res. Public Health 2021,18, 8014. [CrossRef]
42.
Lokka, I.E.; Çöltekin, A. Perspective switch and spatial knowledge acquisition: Effects of age, mental rotation ability and
visuospatial memory capacity on route learning in virtual environments with different levels of realism. Cartogr. Geogr. Inf. Sci.
2020,47, 14–27. [CrossRef]
43.
Asperholm, M.; Högman, N.; Rafi, J.; Herlitz, A. What did you do yesterday? A meta-analysis of sex differences in episodic
memory. Psychol. Bull. 2019,145, 785. [CrossRef]
44.
Munion, A.K.; Stefanucci, J.K.; Rovira, E.; Squire, P.; Hendricks, M. Gender differences in spatial navigation: Characterizing
wayfinding behaviors. Psychon. Bull. Rev. 2019,26, 1933–1940. [CrossRef]
45.
Erkan, ˙
I. Examining wayfinding behaviours in architectural spaces using brain imaging with electroencephalography (EEG).
Archit. Sci. Rev. 2018,61, 410–428. [CrossRef]
Sustainability 2022,14, 16581 18 of 20
46.
Lu, Z.; Pesarakli, H. Seeing Is Believing: Using Eye-Tracking Devices in Environmental Research. HERD Health Environ. Res. Des.
J. 2022,19, 76–92. [CrossRef]
47.
Shamsuddin, N.A.A.; Din, S.C.; Saruwono, M.; Ahmad, M. A Review on Wayfinding Information in Complex Environment.
Environ.-Behav. Proc. J. 2022,7, 129–134. [CrossRef]
48.
Revell, K.M.; Richardson, J.; Langdon, P.; Bradley, M.; Politis, I.; Thompson, S.; Stanton, N.A. Breaking the cycle of frustration:
Applying Neisser’s Perceptual Cycle Model to drivers of semi-autonomous vehicles. Appl. Ergon. 2022,85, 103037. [CrossRef]
49.
Symonds, P.; Brown, D.H.; Lo Iacono, V. Exploring an absent presence: Wayfinding as an embodied sociocultural experience.
Sociol. Res. Online 2017,22, 48–67. [CrossRef]
50.
Alkouri, Z. Developing spatial abilities in young children: Implications for early childhood education. Cogent Educ.
2022
,9, 1–9.
51.
Pullano, L.; Foti, F. The development of human navigation in middle childhood: A narrative review through methods, Terminol-
ogy, and fundamental stages. Brain Sci. 2022,12, 1079. [CrossRef]
52. Peer, M.; Brunec, I.K.; Newcombe, N.S.; Epstein, R.A. Structuring knowledge with cognitive maps and cognitive graphs. Trends
Cogn. Sci. 2021,25, 37–54.
53.
Afonso-Jaco, A.; Katz, B.F. Spatial Knowledge via Auditory Information for Blind Individuals: Spatial Cognition Studies and the
Use of Audio-VR. Sensors 2022,22, 4794. [CrossRef]
54.
Behrens, T.E.; Muller, T.H.; Whittington, J.C.; Mark, S.; Baram, A.B.; Stachenfeld, K.L.; Kurth-Nelson, Z. What is a cognitive map?
Organizing knowledge for flexible behavior. Neuron 2018,100, 490–509.
55.
Bottini, R.; Doeller, C.F. Knowledge across reference frames: Cognitive maps and image spaces. Trends Cogn. Sci.
2020
,24, 606–619.
[CrossRef]
56.
Weisberg, S.M.; Newcombe, N.S. How do (some) people make a cognitive map? Routes, places, and working memory. J. Exp.
Psychol. Learn. Mem. Cogn. 2016,42, 768–785.
57.
Ericson, J.D.; Warren, W.H. Probing the invariant structure of spatial knowledge: Support for the cognitive graph hypothesis.
Cognition 2020,200, 104276. [CrossRef] [PubMed]
58.
Filomena, G.; Verstegen, J.A. Modelling the effect of landmarks on pedestrian dynamics in urban environments. Comput. Environ.
Urban Syst. 2021,86, 101573. [CrossRef]
59.
Yousif, S.R. Redundancy and reducibility in the formats of spatial representations. Perspect. Psychol. Sci.
2022
,17, 1778–1793.
[CrossRef] [PubMed]
60.
Bouchekioua, Y.; Blaisdell, A.P.; Kosaki, Y.; Tsutsui-Kimura, I.; Craddock, P.; Mimura, M.; Watanabe, S. Spatial inference without a
cognitive map: The role of higher-order path integration. Biol. Rev. 2021,96, 52–65. [CrossRef]
61.
Chang, J.H.; Leung, Y.C. Dynamic image clustering from projected coordinates of deep similarity learning. Neural Netw.
2022
,152,
1–16. [CrossRef]
62.
Siew, C.S.; Wulff, D.U.; Beckage, N.M.; Kenett, Y.N. Cognitive network science: A review of research on cognition through the
lens of network representations, processes, and dynamics. Complexity 2019,2019, 2108423. [CrossRef]
63.
Taub, M.; Azevedo, R. Using Sequence Mining to Analyze Metacognitive Monitoring and Scientific Inquiry Based on Levels of
Efficiency and Emotions during Game-Based Learning. J. Educ. Data Min. 2018,10, 1–26.
64.
Ahmadpoor, N.; Shahab, S. Spatial knowledge acquisition in the process of navigation: A review. Curr. Urban Stud.
2019
,7, 1–19.
[CrossRef]
65.
Klahr, D.; Wallace, J.G. Cognitive Development: An Information-Processing View, 1st ed.; Lawrence Erlbaum Associates: Washington,
DC, USA, 2022; p. 244.
66. Neisser, U. Cognitive Psychology, 1st ed.; Taylor & Francis: Abingdon, UK; Psychology Press: New York, NY, USA, 2014; p. 348.
67.
Ritter, F.E.; Tehranchi, F.; Oury, J.D. ACT-R: A cognitive architecture for modeling cognition. Wiley Interdiscip. Rev. Cogn. Sci.
2019
,
10, e1488. [CrossRef]
68.
Kotseruba, I.; Gonzalez, O.J.A.; Tsotsos, J.K. A review of 40 years of cognitive architecture research: Focus on perception, attention,
learning and applications. arXiv 2016, arXiv:1610.08602.
69. Malmberg, K.J.; Raaijmakers, J.G.; Shiffrin, R.M. 50 years of research sparked by Atkinson and Shiffrin (1968). Mem. Cogn. 2019,
47, 561–574. [CrossRef] [PubMed]
70.
Ruggiero, G.M.; Spada, M.M.; Caselli, G.; Sassaroli, S. A historical and theoretical review of cognitive behavioral therapies: From
structural self-knowledge to functional processes. J. Ration.-Emot. Cogn.-Behav. Ther. 2018,36, 378–403. [CrossRef] [PubMed]
71.
Eppe, M.; Gumbsch, C.; Kerzel, M.; Nguyen, P.D.; Butz, M.V.; Wermter, S. Intelligent problem-solving as integrated hierarchical
reinforcement learning. Nat. Mach. Intell. 2022,4, 11–20. [CrossRef]
72.
Van Tilburg, W.A.; Igou, E.R. Moving onwards: An action continuation strategy in finding the way. J. Behav. Decis. Mak.
2014
,27,
408–418. [CrossRef]
73.
Campbell, J.I.; Hepner, I.J.; Miller, L.A. The influence of age and sex on memory for a familiar environment. J. Environ. Psychol.
2014,40, 1–8. [CrossRef]
74.
Chen, M.X.; Chen, C.H. User experience and map design for wayfinding in a virtual environment. In Proceedings of the
International Conference on Human-Computer Interaction, Orlando, FL, USA, 26–31 July 2019; pp. 117–126.
75.
Gagnon, K.T.; Thomas, B.J.; Munion, A.; Creem-Regehr, S.H.; Cashdan, E.A.; Stefanucci, J.K. Not all those who wander are lost:
Spatial exploration patterns and their relationship to gender and spatial memory. Cognition 2018,180, 108–117. [CrossRef]
Sustainability 2022,14, 16581 19 of 20
76.
Casey, B.M. Individual and group differences in spatial ability. In Handbook of Spatial Cognition, 1st ed.; Waller, D., Nadel, L.L.,
Eds.; American Psychological Association: Washington, DC, USA, 2013; Volume 1, pp. 134–137.
77.
Vizzari, G.; Crociani, L.; Bandini, S. An agent-based model for plausible wayfinding in pedestrian simulation. Eng. Appl. Artif.
Intell. 2020,87, 103241. [CrossRef]
78.
Khasraghi, G.S. Developing a Multi-Agent Based Simulation Model of Users’ Wayfinding as a Representation and PostOccupancy
Evaluation (POE) Tool in a Hospital. Prometheus 2020,4, 102–105.
79. Denis, M. Space and Spatial Cognition—A Multidisciplinary Perspective, 1st ed.; Taylor & Francis: London, UK, 2017; p. 258.
80.
Yassin, M.; El Antably, A.; Abou El-Ela, M.A. The others know the way: A study of the impact of co-presence on wayfinding
decisions in an interior virtual environment. Autom. Constr. 2021,128, 103782. [CrossRef]
81.
Forlizzi, J.; Barley, W.C.; Seder, T. Where should I turn moving from individual to collaborative navigation strategies to inform
the interaction design of future navigation systems. In Proceedings of the Conference on Human Factors in Computing Systems
SIGCHI, New York, NY, USA, 7–10 April 2010; pp. 1261–1270.
82.
Haddington, P. Action and space: Navigation as a social and spatial task, in Space in Language and Linguistics. Geogr. Interact.
Cogn. Perspect. 2013,6, 411–433.
83.
He, G.; Ishikawa, T.; Takemiya, M. Collaborative navigation in an unfamiliar environment with people having different spatial
aptitudes. Spat. Cogn. Comput. 2015,15, 285–307. [CrossRef]
84.
Haghani, M.; Sarvi, M. Following the crowd or avoiding it? Empirical investigation of imitative behavior in emergency escape of
human crowds. Anim. Behav 2017,124, 47–56. [CrossRef]
85.
Bae, C.J.H. Paired Social Wayfinding: Dyadic Interaction in Real-World Navigation. Ph.D. Thesis, Doctor of Philosophy. University
of California, Santa Barbara, CA, USA, September 2020.
86.
Hutchins, E. The distributed cognition perspective on human interaction. In Roots of Human Sociality, 1st ed.; Taylor & Francis:
London, UK, 2006; Volume 1, pp. 375–398.
87.
Li, H.; Thrash, T.; Hölscher, C.; Schinazi, V.R. The effect of crowdedness on human wayfinding and locomotion in a multi-level
virtual shopping mall. J. Environ. Psychol. 2019,65, 101320. [CrossRef]
88.
Loomis, J.M.; Golledge, R.G.; Klatzky, R.L.; Marston, J.R. Assisting wayfinding in visually impaired travelers. In Applied Spatial
Cognition, 1st ed.; Taylor & Francis: London, UK, 2007; Volume 6, pp. 179–202.
89.
Denis, M.; Michon, P.E.; Tom, A. Assisting pedestrian wayfinding in urban settings: Why references to landmarks are crucial in
direction-giving. In Applied Spatial Cognition, 1st ed.; Alen, G.L., Ed.; Psychology Press: New York, NY, USA, 2020; Volume 1, p. 414.
90.
Nair, V.; Olmschenk, G.; Seiple, W.H.; Zhu, Z. ASSIST: Evaluating the usability and performance of an indoor navigation assistant
for blind and visually impaired people. Assist. Technol. 2020,34, 289–299. [CrossRef] [PubMed]
91.
Albarrak, L.; Metatla, O.; Roudaut, A. (Don’t) Mind the Step: Investigating the Effect of Digital Social Cues on Navigation
Decisions. Proc. ACM Human-Comp. Interact. 2021,5, 492. [CrossRef]
92. Barker, A. Navigating life: A taxonomy of wayfinding behaviours. J. Navig. 2019,72, 539–554. [CrossRef]
93.
Colenberg, S.; Jylhä, T.; Arkesteijn, M. The relationship between interior office space and employee health and well-being–a
literature review. Build. Res. Inf. 2021,49, 352–366. [CrossRef]
94. American Society of Interior Design (ASID). Available online: https://www.asid.org/ (accessed on 1 April 2022).
95.
Shi, Y.; Zhang, Y.; Wang, T.; Li, C.; Yuan, S. The effects of ambient illumination, color combination, sign height, and observation
angle on the legibility of wayfinding signs in metro stations. Sustainability 2020,12, 4133. [CrossRef]
96.
Wänström Lindh, U.; Jägerbrand, A.K. Perceived lighting uniformity on pedestrian roads: From an architectural perspective.
Energies 2021,14, 3647. [CrossRef]
97. Suzer, O.K.; Olgunturk, N.; Guvenc, D. The effects of correlated colour temperature on wayfinding: A study in a virtual airport
environment. Displays 2018,51, 9–19. [CrossRef]
98.
Dastgheib, S. Light and Perception of Safety In-Between Buildings: The Role of Lighting in Perception of Safety from a Female
Perspective in In-Between Spaces of Residential Areas. Master’s Thesis, Master’s Programme Architectural. KTH Royal Institute
of Technology, Stockholm, Sweden, May 2018.
99.
Bock, O.; Fricke, M.; Koch, I. Human wayfinding in the horizontal versus vertical plane. J. Environ. Psychol.
2020
,70, 101446.
[CrossRef]
100.
Nasir, N.A.B.A.; Hassan, A.S.; Khozaei, F.; Nasir, M.H.B.A. Investigation of spatial configuration management on social distancing
of recreational clubhouse for COVID-19 in Penang, Malaysia. Int. J. Build. Pathol. Adapt. 2020,39, 782–810. [CrossRef]
101.
Salawu, A.; Muhammad, I.B.; Abdul, A.I.; Momoh, A.S. Influence of Spatial Layout on Wayfinding Behaviour in Hospital
Environment in Nigeria. J. Art Archit. Built Environ. 2020,3, 26–44.
102.
Natapov, A.; Kuliga, S.; Dalton, R.C.; Hölscher, C. Linking building-circulation typology and wayfinding: Design, spatial analysis,
and anticipated wayfinding difficulty of circulation types. Archit. Sci. Rev. 2020,63, 34–46. [CrossRef]
103.
García-Rosales, G.; Chías Navarro, P.; Miguel Sánchez, M.D.; Castaño Perea, E. Wayfinding systems and color to increase
well-being in healthcare facilities spaces. In Proceedings of the Congreso Internacional de Expresión Gráfica Arquitectónica,
Alicant, Spain, 30 May–1 June 2018; pp. 1399–1410.
104.
Mahmood, F.J.; Tayib, A.Y. Healing environment correlated with patients’ psychological comfort: Post-occupancy evaluation of
general hospitals. Indoor Built Environ. 2021,30, 180–194. [CrossRef]
Sustainability 2022,14, 16581 20 of 20
105.
Kumar, P.N.; Betadur, D. Study on mitigation of workplace violence in hospitals. Med. J. Armed Forces India
2020
,76, 298–302.
[CrossRef]
106.
Jue, K.; Nathan-Roberts, D. How Noise Affects Patients in Hospitals. In Proceedings of the Human Factors and Ergonomics
Society Annual Meeting, Los Angeles, CA, USA, 16–20 November 2019; pp. 1510–1514.
107.
de Lima Andrade, E.; da Cunha e Silva, D.C.; de Lima, E.A.; de Oliveira, R.A.; Zannin, P.H.T.; Martins, A.C.G. Environmental
noise in hospitals: A systematic review. Environ. Sci. Pollut. Res. 2021,28, 19629–19642. [CrossRef]
108.
Arabacı, A.; Önler, E. The effect of noise levels in the operating room on the stress levels and workload of the operating room
team. J. PeriAnesth. Nurs. 2021,36, 54–58. [CrossRef]
109.
Hunter, S. Spatial Orientation, Environmental Perception and Wayfinding. Design Resources. 2010. Available online: https://
spatialtypographyblog.wordpress.com/2016/02/23/spatial-orientation-environmental-perception-and-wayfinding/ (accessed
on 23 February 2016).
110.
Hegarty, M.; Keehner, M.; Cohen, C.; Montello, D.R.; Lippa, Y. The role of spatial cognition in medicine. In Applications for Selecting
and Training Professionals, 1st ed.; Applied Spatial Cognition; Psychology Press: London, UK, 2007; pp. 285–316.
111.
Kavanagh, A.; Dickinson, H.; Carey, G.; Llewellyn, G.; Emerson, E.; Disney, G.; Hatton, C. Improving health care for disabled
people in COVID-19 and beyond: Lessons from Australia and England. Disabil. Health J. 2021,14, 101050. [CrossRef]
112.
Mahmoud, E.S.; Mousa, M.G.S. The Role of Atriums and Courtyards in Improving Natural Light and Ventilation in Hospitals.
MEJ. Mansoura Eng. J. 2020,44, 1–15.
113.
Rafeeq, D.A.; Mustafa, F.A. Evidence-based design: The role of inpatient typology in creating healing environment, hospitals in
Erbil city as a case study. Ain Shams Eng. J. 2021,12, 1073–1087. [CrossRef]
114.
Min, Y.H.; Ha, M. Contribution of colour-zoning differentiation to multidimensional spatial knowledge acquisition in symmetrical
hospital wards. Indoor Built Environ. 2021,30, 787–800. [CrossRef]
115.
Johanes, M.; Yatmo, Y.A. Application of visibility analysis and visualisation in hospital wayfinding sign design. DIMENSI: J.
Archit. Built Environ. 2018,45, 1–8. [CrossRef]
116.
McGee, B.; Park, N.K. Colour, Light, and Materiality: Biophilic Interior Design Presence in Research and Practice. Interiority
2022
,
5, 27–52. [CrossRef]
117.
´
Cur
ˆ
ci´c, A.; Kekovic, A.; Ran ¯
delovi´c, D.; Momcilovic-Petronijevic, A. Effects of color in interior design. Zb. Rad. Gra ¯
dev. Fak.
2019
,
35, 867–877.
118.
Harper, C.; Duke, T.; Avera, A.; Crosser, A.; Jefferies, S.; Klisans, D.V. Exploring Hospital Wayfinding Systems: Design Guidelines
for Wayfinding Interfaces. In Proceeding of the International Conference on Applied Human Factors and Ergonomics AHFE,
Online, 25–29 July 2021; pp. 30–36.
119.
Kim, I.J. Hospital flooring safety and health: Knowledge gaps and suggestions. Int. J. Occup. Saf. Ergon.
2021
,27, 1116–1135.
[CrossRef]
120.
T’ing, L.C.; Moorthy, K.; Kee, H.W.; Yee, C.W.; Yee, L.W.; Ni, O.A.; Ting, Y.W. Service quality and outpatients satisfaction in public
hospitals in Malaysia. Int. J. Public Policy Adm. Res. 2019,6, 57–73. [CrossRef]
121.
ARIFFIN, A.A.M.; ZAIN, N.M.; MENON, B.V.; AZIZ, N.A. The Customer Satisfaction Index Model: An Empirical Study of the
Private Healthcare Sector in Malaysia. J. Asian Financ. Econ. Bus. 2022,9, 93–103.
122.
Capolongo, S.; Gola, M.; Brambilla, A.; Morganti, A.; Mosca, E.I.; Barach, P. COVID-19 and healthcare facilities: A decalogue of
design strategies for resilient hospitals. Acta Bio Med. Atenei Parm. 2020,91, 50.
123.
Azzopardi-Muscat, N.; Brambilla, A.; Caracci, F.; Capolongo, S. Synergies in design and health. The role of architects and urban
health planners in tackling key contemporary public health challenges. Acta Bio Med. Atenei Parm. 2020,91, 9.
124. Mandel, L.H.; LeMeur, K.A. User wayfinding strategies in public library facilities. Libr. Inf. Sci. Res. 2018,40, 38–43. [CrossRef]
125.
Qing, Z.; Sun, C.; Reneker, J. Evaluation of airport wayfinding accessibility with the use of a wheelchair simulator. Transp. Res.
Rec. 2021,2675, 52–60. [CrossRef]
126.
Jiang, S.; Allison, D.; Duchowski, A.T. Hospital Greenspaces and the Impacts on Wayfinding and Spatial Experience: An Explorative
Experiment Through Immersive Virtual Environment (IVE) Techniques. HERD Health Environ. Res. Des. J.
2022
,15, 47–60. [CrossRef]
[PubMed]
127.
Mustikawati, T.; Yatmo, Y.A.; Atmodiwirjo, P. Tours and Maps Operations as Movement Mechanism in Indoor Wayfinding. Int. J.
Technol. 2021,12, 887–896. [CrossRef]
128.
En, C.; bin Bebit, M.P. Analysis of the existing healthcare signages for the elderly in Kota Kinabalu: For effective healthcare
signages. J. Gendang Alam (GA) 2021,9, 1–20.
129.
Zijlstra, E.; Hagedoorn, M.; van der Schans, C.; Mobach, M.P. The patient journey in a hospital environment. In Proceedings of
the Companion Proceedings of EFMIC 2020, Online, 1 October 2020; p. 59.
130.
Chen, M.S.; Ko, Y.T.; Hsieh, W.C. Exploring the Planning and Configuration of the Hospital Wayfinding System by Space Syntax:
A Case Study of Cheng Ching Hospital, Chung Kang Branch in Taiwan. Int. J. Geo-Inf. 2021,10, 570. [CrossRef]
131.
Mundher, R.; Abu Bakar, S.; Al-Helli, M.; Gao, H.; Al-Sharaa, A.; Mohd Yusof, M.J.; Aziz, A. Visual Aesthetic Quality Assessment
of Urban Forests: A Conceptual Framework. Urban Sci. 2022,6, 79. [CrossRef]
132.
Mundher, R.; Abu Bakar, S.; Maulan, S.; Yusof, M.J.M.; Al-Sharaa, A.; Aziz, A.; Gao, H. Aesthetic Quality Assessment of
Landscapes as a Model for Urban Forest Areas: A Systematic Literature Review. Forests 2022,13, 991. [CrossRef]
Available via license: CC BY 4.0
Content may be subject to copyright.