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J. People Plants Environ > Volume 27(3); 2024 > Article
Jang, Kang, Suh, Seo, and Ahn: Psychological and Physiological Changes in Firefighters Based on Roadside Flowerscape Models and Plant Colors

ABSTRACT

Background and objective: This study was conducted to examine the psychological and physiological changes in firefighters according to roadside flowerscape (RFS) models and color stimulation.
Methods: EEG and ECG measurement was taken and a survey was conducted on a total of 30 firefighters with a mean age of 35.3 ± 9.4 years in Jeonju.
Results: For the violet RFS among the four colors (white, yellow, pink, and violet) of the RFSs, RST(radio of SMR to theta), RSMT(ratio to mid beta to theta), RMT(ratio of mid beta to theta), RMB(relative mid beta power spectrum), and ASEF(spectral edge frequency of 50% alpha spectrum band), which is a comfort indicator, were the highest in all lobes, including the prefrontal lobe, a finding which was statistically significant. The radio of alpha to high beta (RAHB), an indicator of calm and relaxation, was the highest for the white flowerscape. As for the level of gardening activity, the higher the age, the higher the average monthly income and rank, and the longer work experience, the higher the average value. The stress level of firefighters was 46.7%, indicating the need for expert help. Among the four colors (white, yellow, pink, and violet) of the RFSs, the preference for the yellow flowerscape was the highest, and “pleasant” was also the most common emotion, a finding which was statistically significant. As for the correlation between loyalty to the RFSs and key variables, a positive correlation was found between loyalty and gardening activity level, while a negative correlation was found between loyalty and job burnout. By examining the effects of key variables, as well as demographic variables such as gardening activity level and job burnout on respondents’ loyalty, a sense of calm was found to be the most influential variable.
Conclusion: Based on these findings, it is expected that supporting the development of RFS models and improving a sense of calm and the level of gardening activities, which affect the loyalty of firefighters, who are high-risk workers, will reduce high stress levels and job burnout, and increase interest in plants and psychological and physiological relaxation effects.

Introduction

Firefighters are responsible for protecting people’s lives and property through their response to public emergencies, which can include disaster relief and emergency medical services. Recently, urbanization and economic expansion have increased the needs of the people, as well as the number of disasters and emergency patients (Bae and Kim, 2011; Park, 2012). The various stressors that firefighters face cause a level of job stress that can negatively affect their work (Lee and Kim, 2021). Specifically, work-related stress can reduce quality of life by creating a state of psychological tension that leads to negative behaviors (Choi, 2001). Problems related to various safety accidents and post-traumatic stress in firefighters have been identified. However, since the measures to solve them are inadequate (Lee et al., 2017), support is needed to lessen their stress.
Natural environments and plant landscapes have been found to be very effective in reducing people’s stress (Ulrich et al., 1991; Parsons et al., 1998) and improving their quality of life due to the sense of calm that greenery provides (Son et al., 2003). When humans come into contact with plants, their stress is reduced and prevented, and their cognitive function increases through interaction with nature (Herzog et a l., 1997; Yoon et al., 1997). The emotional relaxation items, which seek stress relief and stabilizing effects based on plants, had higher scores than the environment and health items, which promote air purifying functions and the like (Kwak, 2004) as such, just looking at plants gives people peace of mind, helps them relax, and activates their brain function, giving them a feeling of calm, as well as a sense of comfort and happiness (Lee and Son, 1999).
The psychological effects of green spaces and plants are felt through the sensory organs (Oishi et al., 1995; Kim, 1998), but humans receive information from the environment through all five senses, of which the most is received through vision, at about 70% (Whang et al., 1997; Kim and Lee, 2009). Notably, since color in the visual environment is closely related to the emotions and has emotional characteristics, it affects human sensations and emotions, such as making people happy or sad (Kim, 2003). In addition, visual stimulation in humans causes differences not only in emotional responses, but also in brainwave changes (Kim, 1998; Son et al., 1998). Recently, physiological measurements such as electroencephalogram (EEG) and electrocardiogram (ECG) have been used to obtain more objective data on the effects of flower and leaf colors on human psychological changes, but the data are still insufficient. EEG measures the electrical activity of the cerebral cortex by recording and observing brain activity (Jasper, 1958), and is widely used as an indicator of human mental physiology. Based on the structure of the brain, the frontal lobe plays a very important role in intellectual/conceptual planning, personality aspects, and language production; the temporal lobe in auditory stimulation, memory, and language; the parietal lobe in language processes and visual/spatial processes; and the occipital lobe in visual and perceptual functions (KNA, 1997; Simonov, 1997).
All human beings have a desire for contact and communion with nature and an instinct to return to nature (Wilson, 1984). For this reason, there is an urgent need to develop and utilize various approaches or models to easily access the natural environment in daily life, including plants (Lee, 2007). The purpose of this study was to establish a scientific basis for the stress-reducing effects of creating roadside flower gardens inside and outside of firefighters’ workplaces, and to develop and utilize roadside flowerscape (RFS) models that can improve job stress management and psychological relaxation of firefighters by increasing their access to plants.

Research Methods

Subject selection

In this study, we investigated the psychological and physiological changes in firefighters according to RFS models and color stimulation; EEG and ECG measurement and a survey were conducted on a total of 30 subjects with a mean age of 35.3 ± 9.4 years. Subjects were recruited offline from field support staff at a fire station in Jeonju who were willing to actively participate in the experiment. The experiment met the subject selection criteria in the general field of brain research (Son et al., 1998, 1999; Lee, 2009; Jang et al., 2014a), and after fully explaining the research purpose, measurement items, and methods to the subjects, those who signed the research consent form indicating their willingness to voluntarily participate in the experiment were targeted. They were also instructed to abstain from alcohol for 2 days prior to the measurement, and to abstain from stimulant foods and beverages, including green tea and caffeine, which irritate the brain, for 2 hours prior to the measurement.

Laboratory environmental conditions

EEG and ECG measurement and a survey were conducted at Fire Station D in Jeonju from 9:30 am to 4:00 pm, November 1–3, 2023 (Fig. 1). The measurement space (laboratory), a room with ash-gray walls, was 5.0 m long, 4.0 m wide, and 2.6 m high. Outside light was blocked, and fluorescent lights in the ceiling were turned on to eliminate any psychological effects on the subjects. At table height above the floor, the mean illuminance was 16μmol m−2 s−1 (External Solar Electric Quantum Meter, USA), and the temperature and humidity were 24 ± 2°C and 64 ± 5%, respectively.

Experimental method

Seasonal roadside flower gardens were replaced and created to suit the season from April to November 2023, both inside and outside the firefighters’ workplace, which could be viewed by firefighters from the field support team and 119 emergency team of the fire station in Jeonju, employees of the local agricultural technology center, and local residents. After the flower beds were created, the firefighters were able to directly manage and view the flowerscape. However, supplemental plantings, including herbaceous flowers, were performed from time to time depending on the growth status of the plants.

How to watch the video

After creating an RFS representing each of the four colors (white, yellow, pink, and violet), the landscape and planted plants were recorded on video. EEG and ECG measurement was taken, and a survey was conducted, using visual stimulation of a total of four color series of the recorded RFSs and planted plants. At this point, the subjects were allowed to watch the video, using augmented reality (AR) glasses to enhance their level of immersion (Kwon, 2018). The video consisted of 10 frames for each of the four color series of RFS models and the planted plants, and could be viewed for a total of 2 minutes, 12 seconds per frame. The video was set to automatic slide rotation.

Physiological assessment tools

Quantitative EEG and ECG measurement and analysis

Measurements were performed on the subjects using the BIOS-STX device (BioBrain Inc. Daejeon, Korea; Fig. 1). This is an easy-to-use wireless EEG measurement device that allows simultaneous measurement of EEG by specifying a channel in the measurement of ECG. When measuring EEG and ECG, the subject was asked to sit in a comfortable position by leaning on a chair in front of a monitor displaying experimental images of plant colors (Kim, 1998, Jang et al., 2014a). The measuring device was placed 70cm behind the subjects. When the subjects entered the laboratory, they were given a general explanation of the experiment and then asked to sign a consent form to participate in the experiment. While the measuring device was set up for them, the subjects were allowed to familiarize themselves with the experimental environment. For EEG measurement, an 8-channel EEG monitoring headset consisting of a ground electrode (GND) and reference electrodes A1 and A2 was attached to the head; and ECG measurement electrodes were attached to the left and right sides of the chest using disposable electrodes. Subjects were then asked to wear disposable earplugs to control external noise, and AR glasses. In this study, EEG and ECG measurement were conducted in the following order, which was repeated for 4 experimental RFSs (Fig. 2) and took a total of 40 minutes: orientation, wearing the device, EEG and ECG measurement (1–4); color image 1, emotion measurement, wash time; color image 2, emotion measurement, wash time; color image 3, emotion measurement, wash time; color image 4, emotion measurement; and a survey. For visual stimulation, each color series of plant images was randomly arranged to eliminate the effect of order.
EEG analysis in this study was performed using the BioScan software program (BioBrain Inc., Daejeon, Korea). For physiological signal analysis, the power spectrum for each frequency band was obtained from the EEG measurement data using the Fast Fourier Transformation (FFT) algorithm, and compared with the relative power that offsets individual differences. Power spectrum analysis is an analysis method that transforms time-series signals that change with time into the frequency domain, and determines the signal pattern according to the degree of frequency change. In addition, the brain waves were standardized to the mean amount generated at each electrode, and from this, the mean for each electrode was estimated and a brain map was created and reviewed. The brain map showed the trend of electrical energy fluctuations on the cerebral cortex, with the low potential band colored blue and the high potential band colored red.

Psychological assessment tools

The assessment tools for psychological characteristics consisted of gardening activity level, perceived stress level (based on a Korean version of the Perceived Stress Scale), job burnout, loyalty, and color emotion for RFSs based on the Semantic Differential Scale.

Gardening Activity (GA) Scale

After creating seasonal RFSs, the level of gardening activity was surveyed and analyzed to determine firefighters’ experience or perception of flowerscapes and plants. The GA Scale consists of a total of 12 questions, with four questions in each of three sub-factors: gardening experience, plant preferences, and plant-related episodes (RDA, 2017; Jeong et al., 2019). Responses were given on a 7-point Likert scale (1 point: strongly disagree; 7 points: strongly agree), with higher scores indicating a higher level of gardening experience or perception. The Cronbach’s α of the GA Scale used in this study was .920; and the internal consistency (Cronbach’s α) of the three sub-factor questions was .887 for gardening experience, .776 for plant preference, and .934 for plant-related episodes.

A Korean version of the Perceived Stress Scale (PSS:K)

As an assessment tool for psychological characteristics, a Korean version of the Perceived Stress Scale (PSS:K) was used. The PSS:K was adapted by Baek (2010) from Cohen and Williamson’s (1988) Perceived Stress Scale (PSS-10). The ten items of this scale are composed of two factors: negative experiences related to stress and positive experiences based on coping resources. The scores of the responded items are all summed up to determine four levels of stress; the higher the total score, the higher the level of perceived stress. Level 1 is “a normal stress state” with a total score (TS) of 12 or less, in which “the stress factor itself is not serious or is considered good stress.” Level 2 is a stress state with a TS of 13 or higher, in which the individual “has already begun to be affected by stress.” Level 3 is a stress state with a TS of 17 or higher, in which the individual “has an increased possibility of developing a mental illness.” Lastly, Level 4 is a stress state with a TS of 19 or higher, in which the individual “is analyzed to be in need of professional help.” Each question was answered on a 5-point Likert scale (0: strongly disagree; 4: strongly agree). The internal consistency (Cronbach’s alpha) of the scale was .612.

Job burnout (burnout syndrome)

The job burnout scale used in this study was translated and adapted by Shin (2003) from the Maslach Burnout Inventory-General Survey (MBI-GS) developed by Schaufeli et al. (1996) and tested for validity and reliability. The scale consists of a total of 15 questions covering three sub-factors, including emotional exhaustion, cynicism, and reduced occupational self-efficacy, and was administered using a 5-point Likert scale (1 to 5 points). A higher score indicates more severe burnout, and the Cronbach’s α of the scale was .929.

Loyalty

The loyalty scale used was adapted into three questions based on the customer loyalty scale proposed by Gremler (1995) to fit the situation of RFSs in this study. Each question was answered on a 5-point Likert scale (1: strongly disagree to 5: strongly agree). The Cronbach’s α of the scale was .907.

Semantic Differential Scale (SD method)

The SD method has been widely used to evaluate landscapes, which are elements that not only change in value according to the subjective preferences and tastes of individuals, but are also difficult to quantify. The SD, developed by Osgood et al. (1952), is a scale for measuring a person’s imaginative space using image adjectives for landscape evaluation (Im, 2009) that describe landscapes or human emotions. Three pairs of emotion words that can be associated with plants, “unpleasant-pleasant,” “artificial-natural,” and “exciting-calming,” were used on a 7-point Likert scale (1: strongly disagree; 7: strongly agree); a higher score indicates a greater sense of comfort, naturalness, and calm (Park, 2010; Kim, 2012). The internal consistency, Cronbach’s α, of the scale in this study was .830.

Statistical analysis

Statistical analyses in this study were performed using IBM SPSS Statistics version 25.0. The reliability of the measurement tools was analyzed by estimating Cronbach’s α. The following analyses were performed on the measured and survey data: repeated measures ANOVA for EEG and ECG; one-way ANOVA for gardening activity level, perceived stress level, simple SD, and plant color preference; Pearson’s correlation analysis for the correlation between firefighters’ loyalty, gardening activity level, perceived stress level, and job burnout; multiple regression analysis for the effects of key variables, including gardening activity level, and demographic variables on loyalty; and frequency analysis for the distribution plot of stress level and loyalty ratio, and sociodemographic characteristics based on general background.

Results and Discussion

Demographic background

After creating seasonal RFS models inside/outside the workplace of firefighters categorized as high-risk workers (March – November 2023), EEG/ECG measurements and a survey were conducted to determine the psychological and physiological changes in firefighters. The demographic details of the subjects are shown in Table 1. In terms of gender, there were 28 males (93.3%) and 2 females (6.7%). By age, those in their 30s (43.3%) were the largest group, followed by those in their 20s (33.3%), 50s (13.3%), and 40s (10.1%). For educational background, university graduates (including those currently enrolled) accounted for the largest share at 63.3%, followed by high school graduates at 36.7%. For average monthly income per household, those earning 3.01–4 million won were the largest group at 63.3%, followed by those earning less than 3 million won (16.7%), 4.01–5 million won (13.3%), and 5 million won or more (6.7%). By rank, firefighters made up the majority at 53.3%, followed by senior firefighters (26.8%), fire lieutenants and above (13.3%), and fire sergeants (6.7%). In terms of work experience, those with 1 to less than 5 years were the largest group at 40.0%, followed by those with less than 1 year (26.7%), and those with 5 to less than 10 years, and those with 10 or more years (16.6% each).

Quantitative EEG and ECG measurement and analysis

Targeting firefighters classified as high-risk workers, changes in brain waves were measured according to seasonal RFS models and plant colors (white, yellow, violet, and pink). Based on this, the mean differences examined (Tables 2 and 3; Figures 2 and 3) were found to be statistically significant in all waves except the relative theta power spectrum (RT). The ratio of SMR to theta (RST), an indicator of comfort and immersion without being aware of it, was highest for the violet series among the four color series of RFSs in the left prefrontal lobe (Fp1) and central parietal lobe (Pz); and the ratio of (SMR–mid beta) to theta (RSMT), an indicator of concentration, was also highest for the violet series in the right temporal lobe (T2), left occipital lobe (O1), central frontal lobe (Fz), and central parietal lobe. The results of these indicators were statistically significant.
The ratio of mid beta to theta (RMT) and relative mid beta power spectrum (RMB), which are indicators of concentration, were highest for violet scenery among RFSs in all lobes, including the prefrontal lobe (Fp), which is an indicator of cognition and thinking, as well as creativity (Sokolov, 1963; Kim, 2010), this was statistically significant. The ratio of alpha to high beta (RAHB), an indicator of calm and relaxation, was highest for the white flowerscape in the frontal lobe, which is responsible for functions such as motor activation, intellectual/conceptual planning, and accurate judgment of situations (Kim, 2010) the left occipital lobe (O1), which is responsible for visual/perceptual functions (KNA, 1997) and in the central parietal lobe (Pz), this was statistically significant. However, the spectral edge frequency 95% (SEF95%), an indicator of tension and stress, was highest for the white flowerscape among the RSLs in the occipital lobe (O1 and O2), this was statistically significant. The spectral edge frequency 50% of alpha spectrum band (ASEF), a comfort indicator, was highest for the violet flowerscape in the right prefrontal lobe (Fp2) and the occipital lobe; this was statistically significant. Therefore, it seemed that among the color series of the RFSs, the stabilizing and relaxing effects were felt most strongly for the white flowerscape rather than for the yellow, pink, and violet ones. However, tension was also felt for the white flowerscape. In addition, in almost all lobes, the violet flowerscape appeared to have the highest concentration and comfort effects. These results are similar to the findings of Jang et al. (2014a), who reported tension for a white flowerscape (Tables 2 and 3; Figures 2 and 3) an analysis of human EEG changes in response to white and green flowering plants showed that tension was higher for white than for green flowering plants. Thus, it seems that applying a violet flowerscape model to the workplace of a team that requires comfort or concentration, and a white flowerscape model to the workplace of a team that requires calm and relaxation, can increase the positive effects of creating flowerscapes. However, it would be desirable to apply an RFS model, considering that a flower color preference survey of high-risk occupational groups (Jang et al., 2020; 2023) showed that yellow was the most preferred color, similar to the results of this study.
By examining changes in the autonomic nervous system according to RFS models and colors for firefighters, a high-risk occupational group, it was found that the normalized low frequency (nLF) component, which increases in value when the body is in a state of tension, an indicator of sympathetic nervous system activity, tended to be lowest for the white flowerscape and highest for the violet one. Among the autonomic nervous activities, the normalized high frequency (nHF) component related to the parasympathetic nervous activity, which is an indicator of calm and relaxation, was highest for the white flowerscape and lowest for the violet one. Total power (TP) is the overall activity of the autonomic nervous system, which indicates the ability to adequately cope with internal and external stressors. It was found to be lowest for the white flowerscape and highest for the violet flowerscape of the RFSs. Mean heart rate variability (Mean HRV), which is an indicator of autonomic nervous activity and decreases in a relaxed state, was within the normal pulse range for all four color series (Table 4).

Analysis of psychological characteristics of subjects

Gardening activity level

By examining firefighters’ experience and perception of plants according to their level of gardening activity, it was found that of the three factors of gardening experience, plant preference, and plant-related episodes, the plant-related episodes were the highest (3.40 ± 1.54), followed by plant preference (3.33 ± 1.28), and gardening experience (3.31±1.38; no data provided). Since the level of gardening experience among firefighters was too low compared to the general public (average 4.41/7 points) or experts (average 5.36/7 points), it seemed that they should be given opportunities to come into continuous contact with plants (Jang et al., 2023). Natural environments and plant landscapes have been shown to be very effective in reducing stress (Ulrich et al., 1991; Parsons et al., 1998) or improving the quality of life (Son et al., 2003) of people who are exposed to them because of the sense of calm that greenery provides. Accordingly, it seemed that it would be very desirable to gradually increase the level of firefighters’ gardening activities through RFSs in the future.

A Korean version of the Perceived Stress Scale (PSS:K)

For the perceived stress levels (PSL) of the subjects based on the PSS:K, Level 4, “a state requiring expert help” with a total score (TS) of 19 or higher was the most prevalent, at 46.7%. This was followed by Level 3, “an increased likelihood of developing mental illness” with a TS of 17 or higher (33.3%), Level 2, “a state in which stress has already begun to affect him/her” with a score of 13 or higher (16.7%), and Level 1, “a normal state of stress in which the stressors themselves are not serious or are acceptable as good stress” with a TS of less than 13 (3.3%). 80.0% of all subjects were found to have very high levels of stress: Levels 3 and 4 (Table 5). These results are supported by the finding that the prevalence of post-traumatic stress symptoms among the general public is about 8–26%, while the rate of firefighters’ experiencing traumatic events is over 90% (Shin et al., 2015), of firefighters who have had such experiences, approx. 18–51% have had symptoms of post-traumatic stress (Lee, 2012; Baek, 2014).
When the stress level of firefighters was examined according to age, those in their 30s had the highest stress level (19.2 ± 4.50), followed by those in their 20s at 19.0 (SD = 2.10), those in their 40s at 18.0 (SD = 1.70), and those in their 50s at 16.3 (SD = 5.00), however this was not statistically significant (Table 6). In sum, those in their 20s to 40s are at Level 4, “a state requiring expert help,” which is a very serious level, and those in their 50s are at Level 2, “a state in which stress has already begun to affect the individual.” Park et al. (2019) reported that all age groups (20s to 50s) who participated in a forest therapy program designed to reduce firefighter stress decreased their stress levels. Given their findings, and the findings of this study that the stress of firefighters in their 20s and 40s was at a very serious level, it appears that the use of RFSs would have a positive effect on stress reduction.

Semantic differential scale (SD method)

By examining the psychological effects of the RFS models and colors (white, yellow, pink, violet), including com- fort (unpleasant-pleasant), naturalness (artificial-natural), and calm (exciting-calming), it was found that the sense of comfort was highest for the yellow flowerscape, this was statistically significant (Table 7). Kang et al. (2009) reported that in an emotion survey based on the colors of cut roses, yellow roses were perceived as the clearest, brightest, and freshest. Jang et al. (2020) also reported that in an emotion survey of firefighters regarding plant colors, yellow plants were perceived as the clearest and brightest. These reports support the finding in this study that the yellow flowerscape induced the greatest sense of comfort. Given the findings that firefighters exposed to polluted air and environments at fire scenes felt a great sense of comfort in yellow flowerscapes, the application of yellow flowerscapes, which ranked highest in plant color preference surveys, seems to have a very positive effect.

Loyalty to and preference for roadside flowerscapes (RFSs)

When firefighters were surveyed regarding loyalty to RFSs, Loyalty 1 (being able to speak positively to others about the creation of RFSs) had the highest positive response rate of both “agree” and “strongly agree” at 90%. Loyalty 2 (I think I would like to see RFSs again) and Loyalty 3 (I would strongly recommend the creation of RFSs to my friends and people around me) each had high positive response rates of both “agree” and “strongly agree” at about 70% (Table 8).
When the color preferences for RFSs were surveyed, yellow (4.10 ± 0.71) was the most preferred, followed by white, pink, and violet, although the difference was not statistically significant (Table 9). This result is supported by the following reports. Jang et al. (2020) reported that in a survey of firefighters’ plant color preferences, yellow was the most preferred, followed by white and blue. Jang et al. (2023) reported that in a survey of police officers’ preference for six plant colors, yellow was the most preferred, followed by green, white, blue, orange, and red. Thus, the plant color with the highest preference among firefighters and police officers, high-risk occupational groups, was yellow, which is consistent with the findings of this study. Moreover, Kim and Lee’s (2009) findings that yellow space can be perceived as a spatial element that allows occupants to feel pleasant supports the positive effect of yellow flowerscapes. However, in a survey of the general public on color preferences for landscaping plants, purple was the most preferred color, followed by blue, green, red, white and yellow, which differs from the findings of previous studies and this study. This difference between firefighters and the general public is supported by the report of Jang et al. (2020) that the reason why firefighters do not prefer red flowering plants seems to be related to seeing wounds and blood stains at fire scenes. Furthermore, in the flowerscape preference survey, streetscapes were the most preferred, and Yoon (2021) reported that flowerscapes that can be accessed at any time in daily living spaces such as streets or residential areas are preferred, supporting a positive need for RFSs. Therefore, it seems that when creating flowerscapes around firefighters’ workplaces, a positive effect could be achieved by focusing on the use of yellow plants, for which there is a high color preference.

Correlation between loyalty to roadside flowerscapes and key variables

By examining the correlation between loyalty and key variables depending on RFSs, a positive (+) correlation was found between loyalty and the level of gardening activities, while a negative (−) correlation was found between loyalty and job burnout. In addition, there was a high positive correlation of over 0.6 between stress level and job burnout, which was statistically significant (Table 10). In terms of positive correlations, it appears that as loyalty increases, the level of gardening activities increases, and as stress levels increase, job burnout also increases. Conversely, for negative correlations, it appears that as loyalty increases, job burnout decreases, and as stress levels increase, calmness decreases. Therefore, it seems that as loyalty to RFS increases, the level of gardening activity increases and job burnout decreases. These results were similar to the findings of Jang et al. (2021), who reported that the level of gardening activity appears to have a positive effect on loyalty, as a high correlation was found between the level of gardening activity and the loyalty of firefighters who experienced gardening activities at a care farm. Moreover, in a study of changes in workers’ loyalty before and after experiencing gardening activities (GA) when creating an indoor garden, Jang et al. (2017) reported that the intention to invest in purchasing plants increased after experiencing GA compared to before experiencing GA. Accordingly, it seems that the positive effects of GA can be achieved by increasing accessibility and loyalty to and interest in plants through the direct creation and follow-up management of RFSs among firefighters, who have lower levels of GA than the general public (Jang et al., 2023).

Effects of firefighter key and demographic variables on loyalty

The effects of key variables and demographic variables, a control variable, on loyalty were examined; key variables included level of gardening activity (3 factors: gardening experience, plant preference, and plant-related episodes), stress level, job burnout (3 factors: emotional exhaustion, cynicism, and decreased job self-efficacy), emotions toward plants, and plant color preference. For this purpose, a regression analysis using dummy variables was conducted (Table 11), it was found that cynicism among the job burnout factors, a monthly income of 4.01–5 million won, and the rank of firefighter had a negative effect on loyalty. The variables that have a positive effect on the loyalty of the respondents include: the sense of calm among the emotions towards plants (Pleasant, naturalness, and calm), work experience from 5 to less than 10 years, and among the three factors of GA level, gardening experience and plant preference. In other words, the group with monthly income (MI) of 4.01–5 million won and the rank of firefighter had lower loyalty than those with MI of 4 million won or less or 5.01 million won or more, and the rank of senior firefighter or higher. These variables have a total explanatory power of 90% of loyalty; a sense of calm has the most explanatory power at 43%, followed by gardening experience (19%), cynicism among the job burnout factors (13%), and the group with 5 to less than 10 years of work experience, and plant preference (4% each), and the groups with MI of 4.01–5 million won and the rank of firefighter (3% each). In addition, the F value of 26.27 was statistically significant at the p<.001 level, indicating that the regression equation below was appropriate. Therefore, regarding the relative explanatory power of independent variables that affect respondents’ loyalty, the most influential variable appeared to be a sense of calm on the semantic differential scale for emotion, followed by gardening experience, cynicism, work experience, plant preference, monthly income, and rank. In their analysis of the effects of greenteriors on human psychology, Jang et al. (2014b) reported that spaces with greenteriors were perceived as having a higher sense of calm and naturalness compared to those without greenteriors. Their report supports the findings of this study that a sense of calm was the most significant factor in plant recommendations and repurchase intentions, followed by gardening experience.

Conclusion

This study was conducted to examine psychological and physiological changes in firefighters, a high-risk group for stress, according to roadside flowerscape (RFS) models and color stimulation. EEG measurements and a survey were conducted on a total of 30 firefighters in Jeonju City, with an average age of 35.3 ± 9.4 years. For the the violet RFS among the four colors of RFSs (white, yellow, pink, and violet), RST ( ratio of SMR to theta), RSMT (ratio of (SMR –mid beta) to theta), RMT (ratio of mid beta to theta), RMB (relative mid beta power spectrum), and ASEF (spectral edge frequency 50% of alpha spectrum band), a comfort indicator, were found to be the highest in all lobes, including the prefrontal lobe (Fp), this was statistically significant. RAHB (ratio of alpha to high beta), an indicator of calm and relaxation, was highest for the white RFS. However, SEF95% (Spectral Edge Frequency 95%), which is activated in a tense state, was also high in the white RFS. As for the stress levels of the firefighters, 46.7% of them needed professional help, and those in their 20s and 30s tended to have higher stress levels than those in their 40s and 50s. Their preference tended to be the highest for the yellow RFS, and their sense of comfort was also found to be the highest for the yellow RFS, which was statistically significant. Regarding the correlation between firefighters’ loyalty to the RFSs and key variables, a positive (+) correlation was found between loyalty and level of gardening activity, and a negative (−) correlation was found between loyalty and job burnout. Moreover, a negative correlation was found between stress levels and job burnout (p< .05). Thus, it appears that as loyalty to the RFSs increases, the level of gardening activities increases, while job burnout decreases. The effects of key variables, including level of gardening activity and job burnout, as well as demographic variables on respondents’ loyalty were examined. In terms of the relative explanatory power of the independent variables affecting their loyalty, the most influential variable was found to be a sense of calm on the semantic differential (SD) scale for emotion, followed by gardening experience, cynicism, work experience, plant preference, monthly income, and rank. Based on these findings, it is expected that supporting the development of RFS models and improving a sense of calm and the level of gardening activities, which affect the loyalty of firefighters, who are high-risk workers, will reduce high stress levels and job burnout, and increase interest in plants and psychological and physiological relaxation effects.
In recent years, urbanization has increased the demands and scope of public safety and social services, such as disaster relief and emergency medical services, compared to the past, highlighting the importance of the firefighter’s role and placing more and more responsibility on them. However, therapeutic approaches for the physiological and psychological relaxation of firefighters dealing with these demands and works have not improved significantly.
The limitations of this study and suggestions for future research are as follows. First, since it is directly related to the survival of firefighters deployed in the field, the organizational culture of firefighters has certain characteristics, such as teamwork and hierarchy between upper and lower ranks within the organization. Accordingly, considering their occupational characteristics, it seems very important to use plants suitable for the situation of firefighters, including the most preferred yellow flowerscape, violet flowerscape with a high concentration effect and white flowerscape with a high calming and relaxing effect. Second, as this study conducted for firefighters in Jeonju City lacks the representativeness of a nationwide sample of firefighters and thus requires a multifaceted review, there may be some limitations in the extent to which its findings can be generalized to the population. In the future, positive effects should be determined through continuous research that can produce generalized findings.

Fig. 1
An Experiment with an electroencephalography device: (A) Subject; (B) Measuring device; (C) Positions of 8 electrodes used for electroencephalography measurements (A1 and A2: Reference electrodes, GND: Ground electrode).
ksppe-2024-27-3-189f1.jpg
Fig. 2
Experimental roadside flowerscapes used in the survey. (A) White series: Main color-white, Secondary color-green, Main plant: Nipponanthemum spp. Hydrangea paniculata ‘Red Light’, Anemone hupehensis (B) Yellow series: Main color-yellow, Accent color-violet, Main plant: Achillea millefolium, Lilium Asiatic Hybrids, Eschscholzia californica Cham. (C) Violet series: Main color-violet, Accent color-yellow, Main plant: Salvia farinacea, Caryopteris spp., Buddleja davidii, Aster spp. (D) Pink series: Main color-Pink, Secondary color-violet, Main plant: Zinnia elegans, Sedum spectabile, Echinacea purpurea.
ksppe-2024-27-3-189f2.jpg
Fig. 3
Electroencephalographic (EEG) mapping; blue and red indicate low and high electrical potential, respectively. Electroencephalographic (EEG), RT: Relative theta power spectrum, RST: Ratio of SMR to theta, RMT: Ratio of mid beta to theta, RSMT: Ratio of (SMR–mid beta) to theta, RMB: Relative mid beta power spectrum, SEF95%: Spectral edge frequency 95%, RAHB: Ratio of alpha to high beta, ASEF: Spectral edge frequency 50% of alpha spectrum band. Fp = prefrontal lobes, T = temporal lobe, O = occipital lobes, Fz = frontal central zero, Pz = parietal central zero, odd and even numbers indicate left and right hemispheres, respectively.
ksppe-2024-27-3-189f3.jpg
Table 1
Characteristic of survey respondents (N = 30)
Variable Categories Frequency Percent (%)
Gender Male 28 93.3
Female 2 6.7

Age 20 – 29 10 33.3
30 – 39 13 43.3
40 – 49 3 10.1
50 – 59 4 13.3

Education High school graduate 11 36.7
Univ. graduate 19 63.3
Postgraduate 0 0.0

Monthly income (Won) ≤ 3,000,000 5 16.7
3,010,000 – 4,000,000 19 63.3
4,010,000 – 5,000,000 4 13.3
≥ 5,010,000 2 6.7

Rank Firefighter 16 53.3
Senior firefighter 8 26.7
Fire sergeant 2 6.7
≥ Fire lieutenant 4 13.3

Work type Fire suppression 15 50.0
Rescue 8 26.7
First aid 6 20.0
Administrations 1 3.3

Work experience Less than 1 year 8 26.8
1 to less than 5 years 12 40.0
5 to less than 10 years 5 16.6
10 or more years 5 16.6
Table 2
Changes in participants' EEG for four color series of roadside flowerscapes
EEGz Fp1y Fp2 T3 T4 O1 O2 Fz Pz
RT 2.454 1.984 1.045 0.357 0.047 0.183 1.183 1.115
RST 2.499* 1.388 0.532 2.399 1.819 1.604 2.790 3.433*
RMT 3.299* 3.655* 2.571 4.420** 3.103* 2.074 5.788** 6.114***
RSMT 3.171 3.158 2.113 4.183* 3.080* 2.069 5.165** 5.514**
RMB 6.002** 8.770*** 6.782*** 7.098*** 4.579* 6.790*** 9.073*** 8.323***
SEF95 1.002 0.770 2.129 2.552 4.025* 4.526** 3.414* 2.082
RAHB 3.739* 6.435** 1.168 1.619 3.389* 2.011 3.903* 0.866
ASEF 1.596 3.571* 1.652 1.373 6.495*** 4.936** 0.314 2.566

z Electroencephalographic (EEG), RT: Relative theta power spectrum, RST: Ratio of SMR to theta, RMT: Ratio of mid beta to theta, RSMT: Ratio of (SMR–mid beta) to theta, RMB: Relative mid beta power spectrum, SEF95%: Spectral edge frequency 95%, RAHB: Ratio of alpha to high beta, ASEF: Spectral edge frequency 50% of alpha spectrum band.

y Fp = prefrontal lobes, T = temporal lobe, O = occipital lobes, Fz = frontal central zero, Pz = parietal central zero, odd and even numbers indicate left and right hemispheres, respectively.

* significant at p < .05, respectively, by repeated-measures ANOVA (N = 30).

Table 3
Participants' EEG for four color series of roadside flowerscapes
EEGz Ty Fp1 Fp2 T3 T4 O1 O2 Fz Pz
RT GCx 0.267 ± 0.011w 0.254 ± 0.012 0.124 ± 0.008 0.109 ± 0.005 0.125 ± 0.005 0.142 ± 0.006 0.243 ± 0.009 0.148 ± 0.004
YC 0.254 ± 0.011 0.247 ± 0.011 0.134 ± 0.008 0.113 ± 0.006 0.126 ± 0.005 0.141 ± 0.006 0.235 ± 0.009 0.151 ± 0.006
PC 0.248 ± 0.014 0.236 ± 0.014 0.127 ± 0.008 0.112 ± 0.005 0.125 ± 0.005 0.139 ± 0.006 0.230 ± 0.010 0.145 ± 0.004
VC 0.251 ± 0.012 0.242 ± 0.013 0.131 ± 0.009 0.110 ± 0.005 0.125 ± 0.005 0.141 ± 0.005 0.232 ± 0.010 0.145 ± 0.005
RST GC 0.253 ± 0.014 0.266 ± 0.016 0.558 ± 0.028 0.626 ± 0.022 0.655 ± 0.035 0.572 ± 0.026 0.284 ± 0.015 0.489 ± 0.014
YC 0.267 ± 0.014 0.277 ± 0.017 0.559 ± 0.038 0.641 ± 0.030 0.651 ± 0.032 0.585 ± 0.027 0.294 ± 0.014 0.483 ± 0.016
PC 0.282 ± 0.019 0.295 ± 0.022 0.566 ± 0.025 0.625 ± 0.021 0.658 ± 0.037 0.586 ± 0.027 0.299 ± 0.016 0.498 ± 0.015
VC 0.278 ± 0.017 0.289 ± 0.019 0.579 ± 0.033 0.671 ± 0.027 0.683 ± 0.036 0.605 ± 0.027 0.308 ± 0.017 0.519 ± 0.017
RMT GC 0.398 ± 0.032 0.436 ± 0.044 1.189 ± 0.075 1.351 ± 0.082 1.250 ± 0.084 0.879 ± 0.040 0.454 ± 0.044 0.813 ± 0.030
YC 0.423 ± 0.036 0.465 ± 0.045 1.191 ± 0.104 1.339 ± 0.086 1.245 ± 0.081 0.885 ± 0.041 0.488 ± 0.042 0.843 ± 0.037
PC 0.470 ± 0.049 0.512 ± 0.054 1.228 ± 0.082 1.367 ± 0.079 1.274 ± 0.076 0.917 ± 0.034 0.520 ± 0.047 0.892 ± 0.042
VC 0.468 ± 0.041 0.517 ± 0.050 1.357 ± 0.104 1.530 ± 0.086 1.376 ± 0.088 0.959 ± 0.046 0.534 ± 0.045 0.934 ± 0.043
RSMT GC 0.652 ± 0.045 0.702 ± 0.059 1.747 ± 0.098 1.976 ± 0.097 1.905 ± 0.105 1.452 ± 0.060 0.737 ± 0.057 1.301 ± 0.038
YC 0.690 ± 0.049 0.742 ± 0.062 1.749 ± 0.139 1.980 ± 0.110 1.896 ± 0.098 1.470 ± 0.061 0.783 ± 0.055 1.326 ± 0.047
PC 0.753 ± 0.068 0.807 ± 0.075 1.794 ± 0.104 1.992 ± 0.095 1.933 ± 0.098 1.503 ± 0.056 0.820 ± 0.061 1.389 ± 0.051
VC 0.747 ± 0.057 0.805 ± 0.069 1.936 ± 0.135 2.201 ± 0.109 2.060 ± 0.109 1.564 ± 0.065 0.843 ± 0.059 1.453 ± 0.054
RMB GC 0.097 ± 0.004 0.098 ± 0.004 0.135 ± 0.006 0.139 ± 0.006 0.149 ± 0.008 0.120 ± 0.004 0.101 ± 0.005 0.118 ± 0.004
YC 0.097 ± 0.004 0.102 ± 0.004 0.139 ± 0.006 0.140 ± 0.006 0.150 ± 0.007 0.120 ± 0.004 0.106 ± 0.005 0.123 ± 0.004
PC 0.099 ± 0.004 0.102 ± 0.004 0.144 ± 0.007 0.146 ± 0.006 0.154 ± 0.007 0.124 ± 0.004 0.109 ± 0.005 0.126 ± 0.004
VC 0.105 ± 0.005 0.109 ± 0.005 0.155 ± 0.006 0.158 ± 0.006 0.164 ± 0.007 0.130 ± 0.004 0.114 ± 0.005 0.131 ± 0.004
SEF95 GC 46.243 ± 0.191 46.490 ± 0.186 47.443 ± 0.108 47.587 ± 0.121 47.270 ± 0.141 47.057 ± 0.168 46.637 ± 0.230 47.317 ± 0.224
YC 46.330 ± 0.157 46.463 ± 0.148 47.300 ± 0.114 47.493 ± 0.114 47.203 ± 0.151 47.010 ± 0.157 46.597 ± 0.217 47.327 ± 0.228
PC 46.290 ± 0.186 46.517 ± 0.191 47.357 ± 0.118 47.523 ± 0.106 47.240 ± 0.144 47.003 ± 0.184 46.560 ± 0.217 47.277 ± 0.219
VC 46.157 ± 0.166 46.353 ± 0.141 47.240 ± 0.109 47.397 ± 0.095 46.980 ± 0.141 46.713 ± 0.133 46.243 ± 0.207 47.060 ± 0.222
RAHB GC 1.391 ± 0.088 1.371 ± 0.091 0.930 ± 0.082 1.043 ± 0.096 1.138 ± 0.056 1.207 ± 0.048 1.516 ± 0.086 1.421 ± 0.062
YC 1.388 ± 0.107 1.342 ± 0.097 0.990 ± 0.074 1.027 ± 0.081 1.200 ± 0.076 1.248 ± 0.068 1.492 ± 0.099 1.450 ± 0.072
PC 1.290 ± 0.103 1.212 ± 0.093 0.909 ± 0.065 1.020 ± 0.078 1.125 ± 0.058 1.194 ± 0.051 1.397 ± 0.089 1.391 ± 0.068
VC 1.246 ± 0.084 1.216 ± 0.072 0.916 ± 0.067 0.936 ± 0.068 1.071 ± 0.057 1.148 ± 0.051 1.393 ± 0.073 1.403 ± 0.065
ASEF GC 10.060 ± 0.025 10.063 ± 0.025 10.270 ± 0.028 10.307 ± 0.024 10.327 ± 0.034 10.277 ± 0.030 10.100 ± 0.028 10.227 ± 0.026
YC 10.080 ± 0.023 10.107 ± 0.023 10.280 ± 0.034 10.313 ± 0.029 10.350 ± 0.035 10.297 ± 0.028 10.107 ± 0.024 10.207 ± 0.021
PC 10.097 ± 0.027 10.110 ± 0.028 10.290 ± 0.028 10.313 ± 0.025 10.350 ± 0.035 10.297 ± 0.031 10.110 ± 0.028 10.207 ± 0.026
VC 10.083 ± 0.028 10.100 ± 0.028 10.317 ± 0.038 10.340 ± 0.031 10.400 ± 0.038 10.343 ± 0.032 10.113 ± 0.027 10.243±0.030

z Electroencephalographic (EEG), RT: Relative theta power spectrum, RST: Ratio of SMR to theta, RMT: Ratio of mid beta to theta, RSMT: Ratio of (SMR–mid beta) to theta, RMB: Relative mid beta power spectrum, SEF95%: Spectral edge frequency 95%, RAHB: Ratio of alpha to high beta, ASEF: Spectral edge frequency 50% of alpha spectrum band.

y T = Treatment, Fp = prefrontal lobes, T = temporal lobe, O = occipital lobes, Fz = frontal central zero, Pz = parietal central zero, odd and even numbers indicate left and right hemispheres, respectively.

x GC: White color, YC: Yellow color, PC: Pink color, VC: Violet color

w Values are mean±standard error (N = 30).

Table 4
Changes in the autonomic nervous system of participants into gardening
Variance Colors of plant F p

White Yellow Pink Violet
nLFz 0.410 ± 0.181y 0.427 ± 0.170 0.479 ± 0.224 0.496 ± 0.223 1.884 .144NS
nHF 0.590 ± 0.181 0.573 ± 0.170 0.521 ± 0.224 0.504 ± 0.223 1.884 .144NS
TP 11.300 ± 1.148 11.376 ± 1.495 11.401 ± 1.322 11.437 ± 1.287 0.217 .852NS
Mean HRV 71.936 ± 12.963 72.302 ± 12.533 72.105 ± 12.440 73.274 ± 11.090 2.554 .065NS

z nLF: normalized Low Frequency, nHF: normalized High Frequency, TP: Total power, Mean HRV: Mean Heart Rate Variability.

y Values are mean ± standard error.

NS Non-significant at p > .05, respectively, by repeated-measures ANOVA (N = 30).

Table 5
Stress level of the subjects (N = 30)
Group N Percent (%)

Stress level Step 1z 1 3.3
Step 2 5 16.7
Step 3 10 33.3
Step 4 14 46.7

Stress score < 13 (step 1) ≤ 13–16 (step 2), ≤ 17–18 (step 3), ≥ 19 (step 4)

z Step 1: In a normal stressful state, when the stress factor itself is not serious or is accepted as good stress; Step 2: A state that has already begun to be affected by stress; Step 3: A state that is get higher likely to develop into a mental illness; Step 4: In need state of professional help.

Table 6
Differences in stress level by age of fire-fighters
Stress level Age F p

20s 30s 40s 50s

19.00 ± 2.11zay 19.23 ± 4.48a 18.00 ± 1.73a 16.25 ± 4.99a 0.718 .550NS

z Values are mean ± standard deviation (N = 30). 5-point Likert scale was used, where 0 = not at all, 4 = very often.

x Mean separation within rows by Tukey's multiple range test, 5% level.

NS Non-significant, at p >.05 by one way ANOVA.

Table 7
The difference of emotional words between the four colors of roadside flowerscapes
Variance Pink White Yellow Violet F-value p-value

SD method Pleasant 5.53 ± 1.07zay 5.60 ± 1.07ab 6.20 ± 0.71b 5.53 ± 1.07a 3.174 .027*
Naturalness 5.53 ± 1.17a 5.67 ± 1.32a 6.00 ± 0.91a 5.37 ± 1.25a 1.578 .199NS
Calm 5.20 ± 1.13a 5.77 ± 1.14a 5.73 ± 0.98a 5.47 ± 0.97a 1.879 .137NS

z Values are mean ± standard deviation.

y Mean separation within columns by Tukey's multiple range test, 5% level.

NS Non-significant,

* Significant at p < .05, by one way ANOVA (N = 30).

Table 8
Firefighters' intention to revisit roadside flowerscapes
Evaluation items Strongly disagree Disagree Average Agree Strongly agree

N % N % N % N % N %
Loyalty 1z 0 0.0 0 0.0 3 10.0 16 53.3 11 36.7
Loyalty 2 0 0.0 0 0.0 6 20.0 14 46.7 10 33.3
Loyalty 3 0 0.0 0 0.0 9 30.0 10 33.3 11 36.7

Note. Loyalty was rated on 5-point scale where 1=strongly disagree, 5=strongly agree (N = 30).

z Loyalty 1: Be able to talk positively to other people to roadside flower beds. Loyalty 2: I think I would like to see the roadside flower beds again. Loyalty 3: Strongly recommend to roadside flower beds to relatives or friends.

Table 9
Preference for four colors of roadside flowerscapes
Color Preference F-value p-value
Violet 3.70 ± 0.88zay 1.184 .319NS
Pink 3.87 ± 0.73a
White 3.90 ± 0.96a
Yellow 4.10 ± 0.71a

z Mean±SD (N = 30), 1: Never preference - 5: Very preference.

y Mean separation within rows by Tukey's multiple range test, 5% level.

Table 10
Correlation between loyalty to roadside flowerscapes and key variables
Variance Loyalty Gardening activity level Stress level Job burnout
Loyaltyz 1
Gardening activity level .530** 1
Stress level .104 −.016 1
Job burnout −.256 −.021 .605*** 1

z Loyalty 1: Be able to talk positively to other people to roadside flower beds. Loyalty 2: I think I would like to see the roadside flower beds again. Loyalty 3: Strongly recommend to roadside flower beds to relatives or friends.

*, **,*** Significant at p < .05 or .01 or .001 respectively (N = 30).

Table 11
The effects of participants' gardening activity level, plant preferences, and key variables on loyalty
Independent variable B β t R2 Change in R2 F
(Constant) 0.90 0.89 26.27***
Calm 0.13 0.55 7.48*** 0.43
Gardening experience 0.15 0.30 3.10** 0.19
Cynicism −0.33 −0.31 −4.40*** 0.13
Work experience (5 to less than 10 years) 0.60 0.34 3.20** 0.04
Plant preference tendency 0.18 0.34 3.74*** 0.04
Monthly income(KRW 4.01 – 5 million) −0.54 −0.28 −2.96** 0.03
Fire suppression −0.28 −0.21 −2.30* 0.03

Dependent variable: Loyalty: 5 = extremely so, 4 = so, 3 = normal, 2 = not so, 1 = extremely not.

*, *** Significant at p < .05 or .001, respectively (N = 30).

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