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Article

Nudge-Based Intervention for Cognitive Enhancement of Elderly in Long-Term Care Facilities During Fire Evacuation According to Urgent-Level Circumstances

1
Convergence Institute of Construction, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
2
A3 Architecture Institute, Kyungpook National University, Daegu 41566, Republic of Korea
3
School of Architectural, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
4
Division of Smart Safety Engineering, Dongguk University-WISE, Gyeongju 38066, Republic of Korea
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(8), 1269; https://doi.org/10.3390/buildings15081269
Submission received: 19 February 2025 / Revised: 5 April 2025 / Accepted: 9 April 2025 / Published: 12 April 2025
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

Abstract

The cognitive ability of the elderly significantly influences evacuation performance in urgent situations. Despite its importance, many fire evacuation studies overlook the impact of cognitive ability on elderly evacuation performance. To address this gap, this study employs multicriteria decision-making to identify nudging factors that enhance the cognitive abilities of the elderly during fire evacuations in long-term care facilities. Based on a literature review, key nudging factors include guidance lights, guide lines, handrails, and guidance equipment, with sub-criteria such as location, color, size, and intervals. Experts from academic and practical fields analyzed the nudging factors, followed by a hybrid analytic hierarchy process (AHP–TOPSIS) analysis. The findings emphasize the necessity of providing auditory information through guidance equipment (e.g., voice evacuation system) in high-level scenarios (practice experts AHP: 0.31) and visual information through the continuous installation of guide lines in strategic locations (academic experts AHP: 0.35) to facilitate efficient evacuation. As a result, this study confirms both the differing and concordant opinions among expert groups while recognizing the absolute necessity of elderly evacuation research and considering the unique challenges that prevent actual evacuation experiments with elderly individuals. By synthesizing these perspectives, the study derives the weights and ranks of nudging factors based on urgent-level circumstances, thereby conducting a quantitative assessment of factors that enhance cognitive ability during elderly evacuation. The findings of this study can serve as a basis for future evacuation policy formulation for elderly-related facilities and, as a derivative effect, contribute to ensuring the life safety of elderly individuals within the local community.

1. Introduction

In societies with aging populations, ensuring safety in long-term care settings, such as convalescent hospitals, is becoming increasingly vital [1]. The elderly, who face challenges in mobility and cognitive functions, are particularly vulnerable during evacuations [2,3,4]. They typically move slower and decide slower than younger groups, owing to physical and cognitive declines, prolonging pre-evacuation and wayfinding times [5,6,7]. Research focusing on these unique characteristics is crucial, yet practical challenges limit experimental and survey-based approaches [8,9,10,11,12,13].
Previous research has shown that targeted support can significantly aid evacuations of the elderly with issues such as deteriorations in sensory functions, walking abilities, and balance and cognitive declines, including judgment impairments and disorientation [5,6,9,10,13,14,15,16,17,18,19,20,21,22,23,24]. These studies suggest that enhancements, such as using walking aids and providing clear evacuation information, can improve mobility and cognitive responses during emergencies [8,10,15,18,21,22,24,25]. Despite these advancements, the impact of this information on cognitive enhancement has not been extensively studied. Additionally, changes in psychological states due to varying urgency levels have been noted as significant influences on elderly behavior during evacuations [1]. Nevertheless, existing studies on elderly evacuation continue to use standardized quantitative variables, such as walking speed, as simulation input data, despite significant variability among elderly individuals depending on their physical capabilities [8,9,10,11,12,13].
The concept of a “nudge”, derived from the theory of affordances, suggests that subtle, non-coercive interventions can effectively alter behavior by simplifying and clarifying necessary actions and information [26,27]. By enhancing cognitive processing, nudges can reduce decision-making time and encourage appropriate evacuation actions. Thus, employing nudge-based strategies could be a promising method to improve evacuation safety by supporting the elderly’s decision-making capabilities through non-invasive cognitive enhancements [26,27].
Therefore, since previous studies did not clearly identify the impact of evacuation information on cognitive enhancement during elderly evacuation and did not adequately consider varying emergency levels, this study aims to identify effective nudging factors for cognitive enhancement in elderly evacuation according to urgent-level circumstances. Various methods, such as guidance lights, guide lines, handrail signs, and voice alarms, are essential for creating a nudge effect [22,24,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48]. We evaluate how the forms of these nudging factors, including continuity [28,29,33], size [22,28,31,36,39,40], color [28,37,43], and height [28,29,30,32,33,35,36,41], influence cognitive enhancement in the elderly. Reflecting expert opinions on elderly care and fire evacuation is crucial [49,50]; hence, this study engages 41 experts, including experts from academic fields (n = 20; firefighting and disaster prevention) and professionals (n = 21) from elderly care facilities.
The study employs a hybrid analytic hierarchy process (AHP), which is a technique for order of preference by similarity to ideal solution (TOPSIS) approach, as the analysis method [51,52,53]. The hybrid AHP–TOPSIS method is suitable for evaluating multiple alternatives against various criteria by determining how closely each alternative aligns with the ideal solution, thus identifying the optimal choice. This method can be applied to evaluate and prioritize the importance of nudging factors (visual and auditory) influencing cognitive enhancement during elderly evacuation based on expert group opinions. It unfolds in five main steps: (1) reviewing the literature to summarize elderly evacuation-related nudging factors and their forms, (2) defining urgent-level circumstances and preparing scenarios, (3) conducting expert surveys, (4) assessing the impact of nudging factors on cognitive enhancement under urgent scenarios, and (5) validating the effects of these factors on elderly evacuation.
The effective provision of evacuation information through nudge-based interventions can enhance the cognitive abilities of the elderly during emergencies. Moreover, using nudging factors can mitigate the adverse effects of psychological state changes caused by emergency scenarios, thus potentially reducing pre-evacuation times by simplifying decision-making processes. This research adopts an “agent”-oriented approach, considering the unique cognitive traits of the elderly under urgent conditions, moving away from generalized simulation inputs. The findings are expected to guide future research on dynamic evacuation signage for the elderly, utilizing effective nudging factors.

2. Nudge-Based Evacuation-Inducing Factors (Nudging Factors)

Prior studies were examined to identify the nudging factors that enhance the cognitive functions of the elderly during fire evacuations. The key findings are summarized in Table 1. The main nudging factors identified are guide lines, guidance lights, handrails, and guidance equipment, with their installation intervals, locations, sizes, and colors serving as specific sub-criteria.
Exit sign systems, such as guide lines and guidance lights, influence evacuation times by their placement, environmental conditions, and the evacuee’s cognitive abilities [32]. Visibility under smoke conditions is crucial, as people rely on these signs to navigate evacuation routes [18]. Floor-level exit signs, in particular, support cognitive processing in smoke-filled environments [27], and clear evacuation signs reduce disorientation and uncertainty in evacuation behavior [18,32].
Research on guidance lights includes aspects such as optimal placement, size, design, and color, which can affect evacuation [18,22,54,55]. Effective guidance light specifications have been determined by considering visual cognition and viewing distance, revealing that response times vary with different color combinations [54,55]. The color of guidance lights carries contextual meanings—green for safety, red for danger, and orange for warning—which can psychologically impact urgency perception [22]. However, unconventional colors may confuse evacuees, and color combinations can render pictograms difficult to interpret, potentially obscuring the guidance light’s function in evacuation assistance [22]. Despite extensive research on guidance light cognition, specific studies focusing on elderly evacuation are lacking.
A guide line influences cognition based on its installation location, color, and size [28,29,30]. The continuity of exit sign markings is crucial; shorter intervals between continuous exit signs enhance evacuee route guidance [28], and positioning them as continuous strips at lower levels along the evacuation route aids proximity guidance [29]. For instance, experiment participants followed a path marked by a line of white dots on a hallway floor [29]. Furthermore, using photoluminescent materials on guide lines can enhance visibility, increasing evacuation speed by up to 50% and reducing total evacuation time by 25% [28]. Guide lines also assist in identifying floor height variations, such as steps [29]. However, the potential of guide lines to influence the cognitive and evacuation behaviors of the elderly remains underexplored.
Handrails, initially used as barrier-free walking aids, now also convey evacuation information [56,57]. During evacuations, over 80% of evacuees rely on handrails for support on stairs [28], indicating their significant role. Marking handrails with continuous information strips has been shown to improve evacuation efficiency [29]. For visually impaired evacuees, braille boards attached to handrails are crucial for obtaining evacuation information [28,58]. Thus, handrails not only aid mobility but also enhance psychological stability, evacuation efficiency, and route cognition [29].
Path guidance devices, fire alarm systems, and voice evacuation systems deliver critical auditory evacuation information. These systems alert occupants about fires and highlight dangers [59,60]. Auditory cues from alarms typically prompt occupants to gather belongings and prepare to evacuate, suggesting that auditory guidance can enhance evacuation efficiency by shortening pre-evacuation times [14,18,61].
Table 1. Derivation of nudging factors by analyzing earlier studies.
Table 1. Derivation of nudging factors by analyzing earlier studies.
LiteratureNudging Factor
Guide LinesGuidance LightHand-RailsPath Guidance DeviceFire Alarm SystemVoice Evacuation System
IntervalLocationColorShapeIntervalHeightColorSize
D’Orazio et al. [28]
Proulx and Bénichou [29]
Kobes et al. [30]
Ran et al. [31]
Kobes et al. [32]
Kubota et al. [33]
ISO 3864-1 [34]
Kubota et al. [35]
Smedberg et al. [36]
Kinateder et al. [37]
Balboa et al. [38]
Li et al. [62]
Kim et al. [39]
Olander et al. [22]
Galea et al. [40]
Zhang et al. [41]
Rigos et al. [42]
Rousek and Hallbeck [43]
Menzemer et al. [24]
Wang et al. [44]
Note: Dots (•) indicate the presence or relevance of the corresponding item in the referenced prior studies.
The literature review revealed that existing research primarily focuses on factors such as guidance lights and guide lines for inducing evacuation, as summarized in Table 1, with fewer studies exploring additional factors. Most research has detailed aspects such as the location and color of guidance lights and guide lines but has not comprehensively evaluated their effectiveness in conveying evacuation information. Moreover, no study has specifically identified factors that can enhance the evacuation cognitive abilities of the elderly. Effective communication of evacuation information requires it to be perceivable, understandable, and persuasive. Thus, this study seeks to identify nudging factors that effectively enhance cognitive abilities during evacuation in the elderly.

3. Methodology

3.1. Intervention Forms of the Nudging Factors

In this study, four main criteria—guidance lights, guide lines, handrails, and guidance equipment—and 15 sub-criteria, representing different forms of nudge-based interventions, were applied to evaluate nudging factors related to elderly evacuation in long-term care facilities. Details of each nudging factor used in this study are outlined in Table 2.

3.2. Scenarios Under Urgent-Level Circumstances

The evacuation process and behaviors during a fire in long-term care facilities vary based on urgent-level circumstances [1]. Under normal conditions, residents exhibit typical walking behaviors [63]. However, in emergency situations, such as building fires, evacuation is influenced by differing psychological [8] and environmental factors [64], as well as the walking speeds of individuals [5,6,7]. It is critical to consider these variations to enhance safety and evacuation efficiency [65]. This study develops scenarios that reflect building, occupant, and fire characteristics to assess evacuation efficiency [66,67] based on insights from previous research [1,65]. Initially, it is necessary to establish scenario objects, such as building occupants [67]. In this study, scenarios focus on “building-occupant” dynamics, reflecting the characteristics of long-term care facilities and their elderly residents under both normal and emergency conditions related to fire risks [67]. These characteristics are informed by fire survey data from earlier studies [68,69]. Table 3 outlines scenarios for three levels of urgent circumstances to explore how nudging factors influence evacuation route recognition and affordances for the elderly.
Figure 1 shows the derivation of nudging factors that enhance cognitive capabilities during elderly evacuations under these circumstances. Four main nudging factors were categorized into sub-intervention forms and evaluated across the three scenarios, identifying key influences on elderly cognitive enhancement based on the level of urgency and specific intervention forms.

3.3. Data Collection

A questionnaire was developed to summarize the nudging factors identified in Section 3.1, focusing on items that promote the safe and rapid evacuation of the elderly in long-term care facilities. The questionnaire incorporated scenarios reflecting urgent-level circumstances. The questionnaire utilized pairwise comparisons of each factor to facilitate hybrid AHP–TOPSIS analysis. The survey was conducted from 7 February to 11 April 2024 in Daegu, Korea, involving 41 experts divided into academic (n = 20) and practical field experts (n = 21). The survey was conducted in Daegu Metropolitan City, Republic of Korea, from 7 February to 11 April 2024. As of 2024, the elderly population aged 65 or older in Daegu accounts for 21.1% of the total population, exceeding the national average of 20% [70]. Notably, Daegu has rapidly transitioned into a super-aged society, making it an appropriate study location that reflects elderly characteristics and necessitates diverse welfare policies. To capture diverse perspectives among decision-makers and enhance the robustness of the decision-making process, expert groups were classified into academic experts and practical field experts. The academic group included professors from four universities specializing in firefighting and disaster prevention, as well as researchers from three disaster and evacuation research institutes. The practical field experts were managers from five elderly care hospitals. Experts were initially contacted by phone to request their cooperation and subsequently visited in person to conduct the surveys, enhancing the reliability of the responses through detailed explanations and face-to-face interactions. Table 4 details the demographic characteristics of the expert groups.

3.4. Hybrid AHP–TOPSIS

Hybrid AHP–TOPSIS is a sophisticated decision-making model that integrates subjective judgments and objective measurements by compensating for the limitations of each model [51,53,71]. This combination of AHP and TOPSIS allows decision-makers to systematically evaluate criteria and alternatives based on expert opinions and data. However, a single criterion is insufficient to assess the levels of factors impacting elderly evacuation. The multicriteria decision-making approach facilitates the evaluation of various criteria, encompassing the visual, auditory, and cognitive aspects relevant to emergency situations.
In this study, expert judgments were analyzed using the hybrid AHP–TOPSIS method to identify the key nudging factors for elderly evacuation. The AHP analysis involved pairwise comparisons to ascertain the relative importance of each alternative, employing Saaty’s scale [52]. The consistency of responses was checked using the consistency index (CI) and consistency ratio (CR), calculated by dividing the CI by the random consistency index (RI). A CR of 0.1 or less indicates consistent responses; a CR of 0.2 or less is considered acceptable [52]. The analysis steps are as follows:
Step 1: Construct a decision matrix with criteria/attributes via pairwise comparison. The matrix is represented as
c = c 11 c 12 c 13 c 1 n c 21 c 22 c 23 c 2 n c n 1 c n 2 c n 3 c n n ,
where cij represents the comparative importance of the ith attribute with respect to the jth attribute vis-a-vis the overall objective.
Step 2: Normalize the decision matrix using
m i j = c i j j = 1 n c i j .
Step 3: Calculate the local weights of the criteria/sub-criteria and test the consistency.
Prepare the weighted normalized decision matrix as follows:
W = [ w i ] n × 1 ,
w h e r e   w i = j = 1 m i j n ,
i = 1,2 , 3 n , j = 1,2 , 3 n .
Calculate the consistency vector CV = [cvi] (i = 1, 2, …, n) used to denote the consistency values for different criteria, where c v i = c w i w i for i = 1, 2, …, n.
Determine the maximum Eigen value λmax using
λ m a x = i = 1 n c v i n .
Calculate the consistency index and consistency ratio. The consistency index is found using
C I = λ m a x n n 1 ,
where n represents the number of criteria. Pairwise comparison is consistently evaluated if the consistency index is 0. The consistency ratio (CR) is calculated to check the consistency using
C R = C I R I
where RI represents the average random index; the value is determined by different orders of pairwise comparison matrix. If the CR value obtained is smaller or equal to 10% or 0.10, the evaluation of the attribute importance is accepted, and the inconsistency is ignored. Otherwise, the evaluators are asked to revisit their judgments to increase consistency.
Step 4: Construct the normalized decision matrix that has attributes with different units. This matrix is transformed into a dimensionless unit that enables comparisons across criteria. The data are normalized as
r i j = x i j x i j 2 ,
where xij represents the value of the ith alternative with respect to the jth criterion for i = 1, …, m; j = 1, …, n.
Step 5: Determine the weighted normalized matrix vij by multiplying each column of the matrix rij by weight wj obtained by AHP.
v i j = w j r i j .
Step 6: Determine the ideal (best) and negative-ideal (worst) solutions using
A * = i m a x v i j j ε J , i m i n v i j j ε J = 1,2 , m = v 1 + , v 2 + , v 3 + , v n + ,
A = i m i n v i j j ε J , i m a x v i j j ε J = 1,2 , m = v 1 , v 2 , v 3 , v n ,
where J = (j = 1, 2, …, n); j is associated with the beneficial attributes, and J′ = (j′ = 1, 2, …, n)/j is associated with the non-beneficial attributes. The maximum value of the benefit attributes and the minimum value of the cost attributes are considered for the positive ideal solution (A*), whereas the minimum value of benefit attributes and the maximum value of cost attributes is considered for the negative ideal solution ( A ).
Step 7: Measure the distance of each alternative from the ideal solution using (for i = 1, 2, …, m)
S i * = j = 1 n ( v i j v j + ) 2 .
The distance from the negative ideal solution is measured as
S i = j = 1 n ( v i j v j ) 2 .
Step 8: Determine the relative closeness to the ideal solution using
C i * = ( S i ) / ( S i * + S i )
Step 9: Rank the set of alternatives according to the relative closeness values Ci* in descending order. A higher relative closeness value is the better alternative.
Figure 2 shows the process used to derive nudging factors influencing elderly evacuation under urgent-level circumstances.

4. Results

4.1. Nudging Factor

This study aims to identify the nudging factors affecting cognitive enhancement among elderly individuals under varying levels of evacuation scenarios through the involvement of expert groups. Considering the uncertainty in responses among expert groups, we evaluated the relative importance of nudging factors through pairwise comparisons based on a quantitative numerical scale. The TOPSIS analysis, based on AHP analysis to ensure evaluation reliability, identified key nudging factors for decision-makers. For the analysis, this study aims to determine the detailed factors of the most effective nudging factors for enhancing elderly cognition across different evacuation scenarios (high-level, low-level, and normal circumstances). Accordingly, four nudging factors were selected as the main criteria. The main and sub-criteria were derived based on the literature review in chapter 2 and are summarized in Table 2 (Section 3.1). The specific scenarios for each evacuation level were established in Section 3.2. The overall hierarchical structure is illustrated in Figure 3.
The consistency ratio (CR) for these factors was verified at 0.1, indicating reliable responses. Table 5 presents the AHP results, highlighting the importance of nudging factors under different urgency circumstances as perceived by academic experts. The analysis differentiated factors critical for high-level, low-level, and normal circumstances. In high-level circumstances, the guide line (0.36), guidance light (0.32), guidance equipment (0.17), and handrail (0.15) were deemed most important. For low-level circumstances, the importance shifted marginally to the guide line (0.37), guidance light (0.23), guidance equipment (0.21), and handrail (0.19). In normal circumstances, the prioritization was the guide line (0.35), guidance equipment (0.24), guidance light (0.21), and handrail (0.20), indicating the consistent relevance of the guide line across all scenarios.
Field experts found guidance equipment (avg. 0.32) and guidance light (avg. 0.27) to significantly enhance cognitive capabilities during evacuations under all conditions, though the guide line (avg. 0.17) and handrail (avg. 0.22) were viewed as less effective.
Overall, guidance lights (avg. 0.26) were considered important for cognitive enhancement, whereas handrails (avg. 0.17) were deemed less crucial for conveying evacuation information. Opinions varied between the expert groups: academic experts rated the guide line highly (avg. 0.35) in contrast to the practical field experts (avg. 0.22). Practical field experts valued guidance equipment more highly (avg. 0.32) compared to academic experts (0.36) under normal circumstances.

4.2. Intervention Forms of Nudging Factors

The analysis of intervention types, or sub-criteria, based on Table 5 shows that the influence of nudging factors on elderly cognitive enhancement during evacuation varies significantly across different urgent-level circumstances and between academic and practice experts.
According to the academic experts’ perspectives, across different scenarios, specific intervention forms emerged as particularly effective. In high-level circumstances, the guide line interval (0.134) was the most impactful, followed by the guidance light interval (0.110), guidance light size (0.088), guidance equipment with a fire alarm system (0.087), guide line location (0.086), and guide line color (0.085). For low-level scenarios, the most effective factors were the guide line interval (0.125) and location (0.114), and the guidance equipment’s fire alarm system (0.094) was also notable. Under normal circumstances, the pattern continued with the guide line interval (0.123) leading, supported by the guidance equipment’s fire alarm system (0.115) and guide line location (0.111). All circumstances revealed the importance of the guide line interventions (interval, location, and color), guidance light interval, and the guidance equipment’s fire alarm system, indicating the significance of continuous information exposure. For auditory-based guidance equipment, the fire alarm system was highlighted as especially effective, assisting the elderly in intuitively recognizing fire emergencies owing to the familiarity of the alarm sound.
According to insights from the practice experts, in high-level circumstances, the guidance equipment’s voice evacuation system (0.205) was deemed most effective, indicating the value of diverse auditory information in emergencies. This was also prominent in low-level scenarios, where the same system (0.165) was most influential, along with guidance light size (0.110) and the guidance equipment’s path guidance device (0.099). In normal circumstances, the guidance equipment with a fire alarm system (0.195) took precedence, reflecting its importance in standard conditions.
Overall, guidance equipment, particularly the voice evacuation system, was identified as crucial, with its importance increasing with the urgency of the scenario. The larger light-emitting surfaces of guidance lights and strategic guide line locations were also emphasized. Additionally, the findings suggest that in high- and low-level circumstances, the voice evacuation system, providing detailed voice information such as ignition points and evacuation paths, can significantly enhance elderly evacuation compared to standard fire alarm alerts.
To facilitate the understanding of the AHP results, Figure 4 shows the influence of the main and sub-criteria of nudging factors, highlighting the differences between expert groups. Factors close to the X and Y axes represent divergent views between the groups. For practice experts, the importance of providing auditory information based on the urgency level is emphasized. Marks near gray-dashed lines indicate factors with similar influence levels across groups, such as the location of the guide line and the size of the guidance light in high-level circumstances, and the interval of the guidance light in low-level circumstances.
Table 6 details the TOPSIS analysis results, which are used to prioritize nudging factors by integrating expert opinions. Across scenarios 1 and 2, similar effective nudging factors were identified. Priority is given to auditory information through guidance equipment (e.g., voice evacuation system, fire alarm system, and path guidance device) during elderly evacuation. The arrangement of the guide line at strategic locations and the use of guidance lights with large light-emitting surfaces are also crucial. In scenario 3, under normal circumstances, the location and interval of guidance equipment and guide lines are highly ranked, while the priority for guidance lights diminishes. Providing information via handrails is found to be relatively effective under normal circumstances. The results suggest that auditory information significantly enhances elderly cognitive capabilities, and the continuity and size of visual information exposure are critical.

5. Discussion

5.1. Nudging Factors in Terms of Cognitive Enhancement During Elderly Evacuation

For effective fire evacuation, it is crucial to first recognize the risk, then enhance cognitive ability through evacuation information, and familiarize evacuees with the evacuation process through education [24]. Providing a guidance system can minimize pre-evacuation delays and trigger evacuation behaviors. However, the impact of education may be limited for evacuation-vulnerable groups such as the elderly, who may struggle with understanding and responding to the guidance system owing to cognitive and functional limitations. Thus, further research is needed to explore these groups’ specific needs and enhance evacuation efficiency [72]. This study examined nudging factors that can improve cognitive abilities related to evacuation and wayfinding [24], focusing on identifying and applying effective nudging factors to aid elderly evacuation [72].
A key finding is elderly cognitive enhancement varies depending on the intervention forms of the nudging factors. Effective nudging interventions, such as interval (continuous strip) and size (light-emitting surface and mark), align with findings that continuous photoluminescent tiles along a path can significantly increase evacuation speed by over 20% [9]. This study confirms that continuous information strips such as guidance light interval, guide line interval, and handrail interval are vital, carrying significant weight.
The size of the light-emitting surface of the guidance light is crucial, but caution is required with the continuity of guidance light placement. There is a risk that the elderly may misinterpret guidance lights installed above exits, potentially leading to erroneous behaviors [73,74,75]. This study’s recommendation to install guidance lights at regular intervals contrasts with previous findings suggesting that lights should only be placed above final exits [73,74,75]. Enhancing the clarity of guidance light pictograms could mitigate these misunderstandings, improving exit and wayfinding recognition.
To improve elderly cognitive abilities, comprehensive information utilizing vision, hearing, and touch is necessary. Auditory cues such as shouting “fire” or sounding an alarm can trigger evacuation by inducing psychological tension and anxiety [49]. Among the guidance equipment, academic experts find the fire alarm system most effective, although it may delay actual evacuation owing to the “cry-wolf effect” [42]. In contrast, practice experts favor the voice evacuation system for enhancing elderly cognition in urgent situations, consistent with a previous research finding that larger buildings benefit from efficient warning systems such as emergency communication systems [76]. These nudging factors offer simple methods to reduce uncertainty in elderly evacuation behavior and decrease evacuation times.

5.2. Elderly Cognitive Enhancement According to Urgent-Level Circumstances

There is a notable difference in evacuation performance between the elderly and younger individuals under varying urgent-level circumstances. These circumstances can significantly influence elderly evacuation behavior, decision-making, and psychological responses [1], indicating the need to consider these factors in elderly evacuation research. In this study, scenarios representing different levels of urgency were utilized to evaluate nudging factors.
Analysis revealed that the intervention forms of nudging factors that affect cognitive enhancement during elderly evacuation differed significantly between urgent (high and low levels) and normal circumstances. However, no significant difference was observed between the high and low urgency levels. This may be attributed to the intense psychological responses—such as tension, anxiety, and impatience—experienced during urgent circumstances. The inability to fully capture the real-time psychological state of the elderly in these scenarios highlights a limitation of this study, as the nudging factors were derived through expert surveys. Future research needs to validate the effectiveness of these factors, considering the specific dynamics of urgent-level circumstances.
Moreover, strong stimuli present in high-urgency scenarios can disrupt cognitive processes, potentially leading to unresponsive or lethargic behavior, such as failing to notice evacuation signs [77] or fainting [49]. Thus, employing evacuation signage that counters the elderly’s typical preference for stability is crucial in high-urgency settings [78]. Evacuation signs cannot ensure elderly cognition in high-level circumstances [1]. Previous research has shown that dynamic signage can significantly enhance cognitive recognition—from 38% to 77%—by providing clearer evacuation cues [22]. Dynamic signs, therefore, hold promise for increasing sensory affordances, making evacuation information more noticeable to the elderly.
This study primarily considered static signs owing to methodological constraints, which may have diluted the perceptual differences between high and low urgency levels. Recognizing this limitation, future research involving experimental investigations with dynamic signage could offer valuable insights into enhancing elderly evacuation effectiveness.

5.3. Bridging the Knowledge Gap Between Academic and Practice Experts

Fire risk awareness, influenced by the individual–environment-risk paradigm, necessitates integrating the insights of diverse expert groups—including the elderly, individuals with fire experience, firefighters, disaster prevention theorists, and fire medical experts [49]. This approach is similar to the methodology of previous studies, which have emphasized understanding various perspectives [49,79,80]. Academic experts often focus on theoretical knowledge, while practice experts engage directly with real-world applications, leading to differing viewpoints. Recognizing and balancing these perspectives, rather than favoring one over the other, is essential [79,80].
Previous studies have highlighted these differences: building and firefighting engineers have varied opinions on fire safety [79], and research on optimal evacuation routes using architectural spaces has shown discrepancies between expert groups [79]. Additionally, surveys on fire risk awareness between the elderly and medical experts have revealed divergent views [49]. Nevertheless, consensus has been achieved on key design factors in building design and disaster prevention planning through extensive expert consultation [79]. Installing firefighting equipment in the right place based on the knowledge of firefighting experts is necessary; however, the concept of evacuation support can be strengthened by reflecting parts recognized through the opinions of experts in each field.
In this study, there was a consensus between academic and practice experts regarding the importance of the continuity and size of auditory and visual information in nudging factors. If implemented in long-term care facilities, these factors could significantly enhance the elderly’s cognition of evacuation information. However, opinions on “guidance equipment” differed: academic experts favored the “fire alarm system” (a traditional warning system) but were skeptical of the “voice evacuation system” based on the assumption that traditional methods are more suitable given the elderly’s information literacy [76]. In contrast, practice experts believed that providing specific auditory information through the “voice evacuation system” could enhance elderly cognitive abilities, as direct, actionable information facilitates quicker decision-making and information acceptance. Addressing these divergent views will require further in-depth analysis of nudging factors to assess their cognitive and functional affordances and usage preferences in supporting elderly evacuation.

6. Conclusions

This study demonstrated that the application of nudging factors based on urgent-level circumstances significantly influences elderly cognitive enhancement during fire evacuations in long-term care facilities. The research utilized a hybrid AHP–TOPSIS method, analyzing responses from groups of academic and practice experts. The findings indicate that differences in understanding nudging factors related to elderly evacuation exist between these groups. Key factors identified include the continuity of information provided by the installation intervals of guide lines and guidance lights, as well as the size of the light-emitting surfaces.
This study found that direct and frequent signage in urgent situations enhances the effectiveness of nudging factors by reinforcing information continuity. Similarly, larger sizes of light-emitting surfaces in guidance lights are beneficial for elderly cognition. Additionally, auditory information was identified as crucial, with notable differences in preferred methods of information delivery. Significantly, this study quantitatively assessed factors that enhance cognitive abilities during elderly evacuations, deriving weights and ranks for various nudging factors. These results can improve evacuation efficiency by addressing the extensive time elderly individuals spend in the pre-evacuation stage, including wayfinding and route selection. This can serve as a basis for establishing evacuation policies in elderly-related facilities and, as a derivative effect, potentially enhance life safety for elderly individuals within the local community. The findings contribute to the development of more accurate elderly agent models for fire evacuation simulations, providing a reliable database for such models. Future research should aim to objectively verify (e.g., pre-evacuation time, response time measurement, etc.) the effectiveness of these nudging factors for elderly residents in long-term care facilities. Furthermore, a personalized approach is deemed necessary for analyzing the effectiveness of nudging factors, considering the cognitive, physical, and sensory differences among elderly individuals. This individualized perspective may contribute to a more precise assessment and implementation of nudging strategies in elderly evacuation scenarios.

Author Contributions

Conceptualization, J.R. and Y.-C.K.; methodology, J.R.; formal analysis, J.R. and S.-K.K.; investigation, J.R. and S.-K.K.; data curation, H.-K.L.; writing—original draft preparation, J.R.; writing—review and editing, W.-H.H. and Y.-C.K.; visualization, S.-K.K. and H.-K.L.; supervision, W.-H.H. and Y.-C.K.; project administration, J.R.; funding acquisition, J.R. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1C1C2007215).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2024-00460627).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

AHPAnalytic Hierarchy Process
TOPSISTechnique for Order of Preference by Similarity to Ideal Solution
avg.Average

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Figure 1. Nudging factors affecting cognitive enhancement during elderly evacuation considering urgent-level circumstances.
Figure 1. Nudging factors affecting cognitive enhancement during elderly evacuation considering urgent-level circumstances.
Buildings 15 01269 g001
Figure 2. Flowchart to derive nudging factors based on urgent-level circumstances using AHP–TOPSIS.
Figure 2. Flowchart to derive nudging factors based on urgent-level circumstances using AHP–TOPSIS.
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Figure 3. AHP hierarchical structure.
Figure 3. AHP hierarchical structure.
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Figure 4. Derivation of nudging factors based on the expert groups. In this figure, LTI, LTH, LTC, LTS, LNI, LNL, LNC, LNS, HI, HC, HSZ, HSP, PA, FA, and VS represent the guidance light interval, guidance light height, guidance light color, guidance light size, guide line interval, guide line location, guide line color, guide line size, handrail interval, handrail color, handrail size, handrail shape, guidance equipment (path guidance device), guidance equipment (fire alarm system), and guidance equipment (voice evacuation system), respectively.
Figure 4. Derivation of nudging factors based on the expert groups. In this figure, LTI, LTH, LTC, LTS, LNI, LNL, LNC, LNS, HI, HC, HSZ, HSP, PA, FA, and VS represent the guidance light interval, guidance light height, guidance light color, guidance light size, guide line interval, guide line location, guide line color, guide line size, handrail interval, handrail color, handrail size, handrail shape, guidance equipment (path guidance device), guidance equipment (fire alarm system), and guidance equipment (voice evacuation system), respectively.
Buildings 15 01269 g004
Table 2. Intervention description of nudging factors.
Table 2. Intervention description of nudging factors.
Main CriteriaSub-Criteria
Guidance lightSign lamp indicating the location of nearby exits or evacuation routesBuildings 15 01269 i001Buildings 15 01269 i002
Evacuation information continuity based on guidance light installation intervalsGuidance light installation height
(a) Interval(b) Height
Buildings 15 01269 i003Buildings 15 01269 i004
Guidance light colorGuidance light size
(c) Color(d) Size
Guide lineLine that emits light, either stored or current, facilitating evacuation in dark environmentsBuildings 15 01269 i005Buildings 15 01269 i006
Evacuation information continuity based on guide line installation intervalsInstallation locations: left and right on the floor, center of the floor, and left and right on the walls
(e) Interval(f) Location
Buildings 15 01269 i007Buildings 15 01269 i008
Guide line colorGuide line shape (arrow, dotted line, and straight line)
(g) Color(h) Shape
HandrailStructure on corridor and stair walls, used as walking support and displaying evacuation informationBuildings 15 01269 i009Buildings 15 01269 i010
Evacuation information continuity based on display intervals on the handrail surfaceDisplay color on the handrail surface
(i) Interval(j) Color
Buildings 15 01269 i011Buildings 15 01269 i012
Display size on the handrail surface Display shape on the handrail surface (arrow, dotted line, and straight line)
(k) Size(l) Shape
Guidance equipmentAuditory device to prompt evacuation and issue fire alarmsBuildings 15 01269 i013Buildings 15 01269 i014Buildings 15 01269 i015
Presence/absence of a path guidance systemTraditional fire alarm system (e.g., fire alarm bell and blaring horns). Presence/absence of a machine that detects smoke or heat and issues a fire alarm.System that allows a designated individual to inform evacuation procedures through speakers. Presence/absence of a system that can deliver real-time emergency information using a voice evacuation system.
(m) Path guidance system(n) Fire alarm system(o) Voice evacuation system
Table 3. Scenarios for urgent-level circumstances.
Table 3. Scenarios for urgent-level circumstances.
ScenarioCircumstanceDescription
Scenario 1High-level circumstanceElderly evacuate early owing to severe fire risks.
Elevators are inoperable.
Continuous fire alarms and alerts guide the evacuation process.
Despite differences in cognition and response to evacuation alerts, the elderly simultaneously move toward the exits.
The presence of fire is clear, prompting immediate evacuation.
Scenario 2Low-level circumstanceFire risks are not immediately threatening; elevators are operational.
Those who cannot walk use elevators; others use stairs.
All exits are open, with less time variance in heading to exits than in high-risk scenarios.
Minor fire anticipated; emergency alerts prompt evacuation.
Scenario 3Normal circumstanceNudging factors recognizable in daily life are emphasized.
Elderly seek exits and elevators without psychological pressure; fewer simultaneous movements.
Departure times to exits are random, with no time constraints.
Table 4. Survey participant sample.
Table 4. Survey participant sample.
VariableItemAcademic Field Experts (n = 20)Practical Field Experts (n = 21)
nPercentage (%)nPercentage (%)
GenderMale1050838
Female10501362
Academic backgroundBachelor’s degree or higher2101885.7
Master’s degree or higher840314.3
Doctoral degree or higher10500
Expert groupsProfessor420--
Research1680--
Field expert--21100
Work experienceLess than one year420--
One to three years945942.8
More than five years7351257.2
Table 5. Weight calculation for main- and sub- criteria using AHP.
Table 5. Weight calculation for main- and sub- criteria using AHP.
ScenarioMain CriteriaWeight of Main CriteriaSub-CriteriaWeight of Sub-CriteriaWeight of Main Criteria X Weight of Sub-Criteria
Academic ExpertsPractical ExpertsAcademic ExpertsPractical ExpertsAcademic ExpertsPractical Experts
WeightRankWeightRank
Scenario 1Guidance light0.317700.25504Interval0.348230.230720.1106320.058848
Height0.190580.231140.0605480.058947
Color0.182160.197060.0578790.0502510
Size0.279040.341080.0886530.086983
Guide line0.357530.24970Interval0.375780.248030.1343510.061935
Location 0.242450.364570.0866850.091032
Color0.238530.213440.0852860.053299
Shape0.143240.173950.05121100.0434313
Handrail0.154460.17936Interval0.400600.253730.0618770.0455012
Color0.206800.265700.03194140.0476511
Size0.263580.339280.04071120.060856
Shape0.129010.141290.01992150.0253415
Guidance equipment0.170310.31590Path guidance device0.283480.218240.04827110.068944
Fire alarm system0.515630.130840.0878140.0413314
Voice evacuation system0.200890.650920.03421130.205621
Scenario 2Guidance light0.233190.31372Interval0.298540.213400.0696160.066946
Height0.211220.236610.04925100.074225
Color0.203660.197370.04749110.061918
Size0.286580.352630.0668270.110622
Guide line 0.367500.24421Interval0.341240.247610.1254010.060469
Location0.310790.318440.1142120.077764
Color0.222120.272150.0816240.066467
Shape0.125850.161800.04624120.0395111
Handrail0.189760.14452Interval0.321540.267000.0610180.0385812
Color0.222330.254950.04218140.0368413
Size0.299180.307310.0567790.0444110
Shape0.156950.170740.02978150.0246715
Guidance equipment0.209550.29755Path guidance device0.335280.335240.0702550.099753
Fire alarm system0.450590.110110.0944230.0327614
Voice evacuation system0.214130.554650.04487130.165031
Scenario 3Guidance light0.210800.25200Interval0.363230.202230.0765650.050969
Height0.261810.244250.0551890.061557
Color0.161290.227070.03399130.057228
Size0.213670.326460.04504110.082263
Guide line0.346750.18296Interval0.356460.209850.1236010.0383914
Location0.320640.344690.1111830.063066
Color0.194410.252940.0674170.0462710
Shape0.128490.192510.04455120.0352215
Handrail0.202440.19867Interval0.384680.227700.0778740.0452311
Color0.162930.219290.03298140.0435613
Size0.296010.332670.0599280.066095
Shape0.156390.220340.03165150.0437712
Guidance equipment0.240000.36637Path guidance device0.215940.216750.05182100.079414
Fire alarm system0.480110.534770.1152220.195921
Voice evacuation system0.303950.248480.0729460.091032
Table 6. TOPSIS analysis results for nudging factors.
Table 6. TOPSIS analysis results for nudging factors.
ScenarioMain CriteriaSub-CriteriaTOPSIS
di+di−CCiRank
Scenario 1Guidance lightInterval0.0270.1900.1267
Height0.0110.1920.05512
Color0.0110.1940.05413
Size0.0280.1790.1346
Guide lineInterval0.0420.1850.1863
Location 0.0300.1750.1465
Color0.0250.1880.1178
Shape0.0120.1940.05911
HandrailInterval0.0200.1890.0979
Color0.0100.1910.04814
Size0.0190.1820.09510
Shape0.0000.1990.00015
Guidance equipmentPath guidance device0.0340.1690.1684
Fire alarm system0.0560.1760.2402
Voice evacuation system0.1940.0260.8811
Scenario 2Guidance lightInterval0.0100.1530.06010
Height0.0100.1530.06011
Color0.0070.1560.04212
Size0.0230.1390.1446
Guide line Interval0.0300.1480.1675
Location0.0300.1410.1754
Color0.0190.1460.1177
Shape0.0040.1590.02314
HandrailInterval0.0120.1550.0739
Color0.0060.1580.03513
Size0.0150.1510.0928
Shape0.0000.1620.00215
Guidance equipmentPath guidance device0.0570.1070.3472
Fire alarm system0.0570.1400.2893
Voice evacuation system0.1560.0240.8681
Scenario 3Guidance lightInterval0.0120.1400.0829
Height0.0070.1400.04712
Color0.0040.1430.02415
Size0.0120.1350.08010
Guide lineInterval0.0330.1340.1964
Location0.0300.1260.1945
Color0.0140.1370.0958
Shape0.0050.1440.03414
HandrailInterval0.0220.1330.1437
Color0.0060.1410.04013
Size0.0240.1240.1626
Shape0.0090.1370.06211
Guidance equipmentPath guidance device0.0400.1070.2713
Fire alarm system0.1470.0001.0001
Voice evacuation system0.1000.0500.6662
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Ryu, J.; Kim, S.-K.; Lee, H.-K.; Hong, W.-H.; Kim, Y.-C. Nudge-Based Intervention for Cognitive Enhancement of Elderly in Long-Term Care Facilities During Fire Evacuation According to Urgent-Level Circumstances. Buildings 2025, 15, 1269. https://doi.org/10.3390/buildings15081269

AMA Style

Ryu J, Kim S-K, Lee H-K, Hong W-H, Kim Y-C. Nudge-Based Intervention for Cognitive Enhancement of Elderly in Long-Term Care Facilities During Fire Evacuation According to Urgent-Level Circumstances. Buildings. 2025; 15(8):1269. https://doi.org/10.3390/buildings15081269

Chicago/Turabian Style

Ryu, Jihye, Sung-Kyung Kim, Hye-Kyoung Lee, Won-Hwa Hong, and Young-Chan Kim. 2025. "Nudge-Based Intervention for Cognitive Enhancement of Elderly in Long-Term Care Facilities During Fire Evacuation According to Urgent-Level Circumstances" Buildings 15, no. 8: 1269. https://doi.org/10.3390/buildings15081269

APA Style

Ryu, J., Kim, S.-K., Lee, H.-K., Hong, W.-H., & Kim, Y.-C. (2025). Nudge-Based Intervention for Cognitive Enhancement of Elderly in Long-Term Care Facilities During Fire Evacuation According to Urgent-Level Circumstances. Buildings, 15(8), 1269. https://doi.org/10.3390/buildings15081269

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