Green – The Color of
Stress Recovery: Stress
after Exposure to Nature
Bachelor Degree Project in Cognitive
Neuroscience
First Cycle 22.5 credits
Spring term 2022
Student: Fatimah Hilal
Supervisor: Andreas Kalckert
Examiner: Sakari Kallio
Natur’s Effect on Stress Recovery
1
Abstract
Nature and greenspaces have been enjoyed throughout history and used for relaxation
purposes. Several theories, such as biophilia and stress recovery theory, suggest nature’s
ability to improve stress recovery. Even though stress helps detect danger and enhances
alertness, it causes fatigue and distortive cognitive functions if prolonged. Nature-based
intervention such as Shinrin-yoku or forest bathing, which refers to relaxing walks in forest
environments, has been recently researched and used to reduce stress in individuals.
The current study is an experimental study aimed at whether attendance in nature is
beneficial for stress recovery. Ten subjects were divided into an experimental group (walks in
nature) and a control group (walks in a city environment). They were tested for stress levels
using heart rate variability (HRV) and the Karolinska exhaustion disorder scale (KEDS)
before and after the walks.
The result demonstrated no significant differences in stress recovery for both
measurements before and after walks in nature compared to walks in a city environment.
Despite that, it did not reject nature’s positive impact on stress recovery. Therefore more
research on nature-based intervention and stress recovery is required.
Keywords: shinrin-yoku, hrv, stress recovery theory, biophilia
Natur’s Effect on Stress Recovery
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Green – The Color of Stress Recovery: Stress after Exposure to Nature
The Hanging Gardens of Babylon are one of several ancient historical evidence of
humans enjoying nature. The beauty of the gardens suggests they were created only for
relaxation purposes. The green-leveled gardens with all sorts of trees, flowers, and vines were
so remarkable and romantic that they became part of the seven wonders of the ancient world
(Cartwright, 2018). Many cutlers throughout time have displayed affection towered nature. It
might be due to nature's several health benefits, especially in relaxation and stress recovery
(Grinde & Grindal Patil, 2009).
Stress Recovery
Stress is physiological and psychological responses to deal and cope with stressful
experiences (Ulrich et al., 1991). The body prepares for energy by releasing steroid hormones
such as cortisol in the endocrine system (Kubakawa et al., 1999). The sympathetic nervous
system gets activated and influences changes in the cardiovascular system, increasing heart
rate and decreasing heart rate variability. Psychological stress responses are poorer
emotional regulation, heightened negative emotions, and changes in cognitive functions
(Thayer et al., 2012; Corazon et al., 2019; Ulrich et al., 1991). Ulrich et al. (1991) mean that
stress recovery also has psycho-physiological components. Physiological stress recovery
involves the parasympathetic nervous system stabilizing the body's cardiovascular functions,
endocrine system, and immune system and returning the body to a hemostasis state.
Psychological stress recovery involves shifting into positive emotions (Corazon et al., 2019).
The brain responds to a stressful stimulus by immediately changing into a
hypervigilance state to optimize attentional processing. The amygdala, which modulates
emotions and detects threats, is especially active. The brain's ability to shift into sensory
alertness when facing stressful situations is an essential adaptive quality. However, if the
brain is constantly in a hypervigilance state, nerve cells in corresponding brain regions get
affected. Prolonged stress leads to dendritic expansion in the amygdala, making it
hyperresponsiveness in emotional regulation. Additionally, shrinkage of dendrites in the
prefrontal cortex (PFC) leads to poorer executive functions such as working memory,
regulating self-related thoughts (rumination), and goal-directed behavior (Henckens et al.,
2012; McEwen & Morrison, 2013).
Stress Assessments
Consequently, prolonged stress and minimal stress recovery often cause several
physical and psychiatric disorders, such as exhaustion disorder (ED). As previously
concluded, it can cause fatigue and distortive cognitive functions. Even though the definition
of stress is often debated, the common understanding of stress is the perception of danger,
Natur’s Effect on Stress Recovery
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fear, and negative emotions. Therefore, introspective questionnaires are a common way of
measuring stress (Croswell & Lockwood, 2020). However, a biomarker for stress would be
beneficial for understanding and assessing stress. Thayer et al. (2012) argue for heart rate
variability (HRV) as a stress biomarker. Thayer et al. (2012) mean that HRV can be an index
of stress-related brain functions. The experience of stress involves complicated sequences of
processes by several psychological and physiological systems that impact each other regularly
and spontaneously. HRV is part of that system and can be used to measure the brain's ability
to control and respond to stress-related input.
HRV is changes in the interval between each heartbeat influenced by the autonomic
nervous system. Increased variability indicates a dominance of the parasympathetic nervous
system and a slower heart rate. A decrease in variability indicates a dominance of the
sympathetic nervous system and a faster heart rate (Thayer et al., 2012).
Thayer et al. (2012) presented brain regions related to HRV using fMRI and PET in a
meta-analysis. They showed that the amygdala and the medial prefrontal cortex (mPFC),
associated with perceiving danger and regulating emotion, are also involved in HRV.
Furthermore, mPFC is essential in regulating behavioral and physiological fear responses
such as heart rate, suggesting HRV as a valuable tool to measure stress (Thayer et al., 2012).
HRV can be measured using time-domain, frequency-domain, or non-linear domain
indexes. Frequency – domain is the distribution of energy or power found within one of four
frequency bands (ultra-low-frequency (ULF), very-low-frequency (VLF), low-frequency (LF),
and high-frequency (HF)). The frequency bands are HR oscillations. Each type of frequency
is used depending on the period of HRV recording. Non-linear indexes operate in the
randomness of the time series and unpredictability of the mechanisms that regulate HRV.
Time-domain quantifies how much HRV is observed during the time in-between each
heartbeat, interbeat intervals (IBI). Some of the parameters used for this domain are the
standard deviation of the IBIs for all sinus beats (SDRR), measured in milliseconds (ms); the
percentage of NN (normalized and filtered IBI) that differ from each other by more than 50
ms (pNN50), and the root mean square of successive differences between normal heartbeats
(RMSSD). RMSSD is measured in ms and is widely used to present the average differences
between each HR. Twenty-four hours of RMSSD dose also correlate with no-linear indexes,
frequency domain parameters, and other time-domain parameters. Lower RMSSD values
indicate lower recovery, and higher RMSSD values indicate higher recovery (Shaffer &
Ginsberg, 2017).
One way of controlling stress has been by pharmacological interventions, such as
serotonin reuptake inhibition (SSRI) (Mitsui Wong et al., 2021). SSRI works by blocking the
reuptake of serotonin, a neurotransmitter that plays an essential role in emotions and mood,
into the presynaptic neuron. Serotonin blocking enhances the amount of serotonin in the
Natur’s Effect on Stress Recovery
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synapse and prolongs its effect (Gazzaniga, 2016). Even though it effectively reduces stress, it
can have several adverse side effects, such as memory loss and suicidal thoughts. Therefore, it
is beneficial to examine and introduce other interventions that help with stress recovery
(Mitsui Wong et al., 2021).
Nature as a Stress Recovery Intervention
According to the stress recovery theory, spending time in nature reduces stress and
helps with stress recovery (Ulrich et al., 1991). In an experiment, Ulrich et al. (1991)
demonstrated that natural settings influence physiological stress reduction responses in
individuals after experiencing a stressful stimulus. He exposed 120 subjects to a stressful
movie, followed by a movie of either natural sceneries (trees and water streams) or urbanized
sceneries (roads and traffic lights). The results showed that different environmental settings
influenced stress recovery differently. Exposure to natural environments had a significant
reduction of stress on all physiological measurements taken, including electrocardiogram
(EKG), pulsetransittime (PTT), and spontaneouskinconductance responding (SCR).
Part of nature's effect on stress recovery branches from psychological evolution
theory. Most of human evolutionary history has occurred in nature, where cognitive features
in the brain have evolved to deal with environmental factors. However, most of us live today
in urbanized cities, perhaps days without experiencing nature. Life in urbanized
environments can include a lot of stressors the brain struggles to cope with. Thus, most
people respond positively in terms of being in nature (Lederborgen et al., 2011; Ulrich et al.,
1991). According to the theoretical hypothesis of biophilia, first presented in a book by
Wilson (1984), human adaptation to natural environments caused us to feel an innate
affection and curiosity toward all living things. People often enjoy green spaces, like having
plants at home, taking walks in parks, or viewing nature scenery on TV or from a window.
One study examining greenspace's effect on well-being indoors showed that offices with
plants reported fewer sick leaves by employers than offices without plants (Grinde & Grindal
Patil, 2009). One therapeutic nature treatment vastly researched is Shinrin-yoku in Japan, or
forest bathing. An outdoor nature intervention of relaxing walks in a forest environment
aiming to impact health outcomes positively. Research on Shinrin-yoku has indicated a
positive effect on stress recovery in several physiological biomarkers, like heart rate
variability (HRV) and cortisol measurements. Moreover, the impact of forest bathing is often
explained based on the biophilia hypothesis (Jones et al., 2021). Greenspaces have a relaxing
and positive effect on many people. Therefore, not experiencing nature enough may
negatively impact our well-being (Lederborgen et al., 2011; Grinde & Grindal Patil, 2009).
Natur’s Effect on Stress Recovery
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Nature's Impact on the Brain
Neuroscientific research has likewise presented nature benefits to stress recovery and
how it directly affects the central nervous system. In an experimental study, Park et al.
(2007) tested cerebral activity related to forest bathing. One group walked in a forest, and a
control group walked in a city environment. The result indicated lower activity in the PFC in
the forest group members than in the city group. The study used near-infrared spectroscopy
(NIS). It measures the concentration of the oxyhemoglobin (oxy-Hb) and the
deoxyhemoglobin (deoxy-Hb) in regional cerebral blood flow. A higher increase of oxy-Hb
relative to deoxy-Hb indicates neural activity. The forest group had less concentration of total
hemoglobin in the PFC. One crossover experiment aiming to research gandingan's effect on
the brain found that transferring plants from one place to another led to less oxy-Hb
concentration in the PFC compared to moving empty pots (Park et al., 2017). All sensory
modalities seem to react positively to nature. For example, olfactory sensations like the scent
of wood also reduce cerebral activity in the PFC (Chen & Nagawga, 2019).
Studies used functional magnetic resonance imaging (fMRI), Which has a higher
spatial resolution, to examine further what happens in deeper brain structures. Within the
PFC structures, the pregenual anterior cingulate cortex (pACC) and subgenual PFC seem to
be more implicated in the well-being and the relaxing effect people experience concerning
nature. In one fMRI study, Bratman et al. (2015) found the pACC and the subgenual PFC less
active after a 90-minute walk in nature. The subgenual PFC is identified to be part of the
default mode network. It is associated with rumination and self-reflective thoughts and gets
mostly active under negative emotions such as sadness, guilt, and rejection. It is identified to
be relatively more active in patients with depression. The pACC's primary role is to inhibit
and regulate amygdala activity, causing functional connectivity between the pACC and the
amygdala, indicating emotional control and evaluation of negative information such as
threats. Lower activation in pACC leads to higher functional connectivity to the amygdala
(Chen & Nagawga, 2019; Lederorgen et al., 2011). Furthermore, upbringing in urbanized
environments demands higher amygdala activation and higher activation of the pACC.
Overactive pACC over time may lead to neural death and shrinkage, which will cause less
emotional control, resilience, and a damaging cycle of neural activity (Chen & Nagawga,
2019).
Associated Stress-Reducing Factors
According to Bratman et al. (2015) and Park et al. (2007), walks in nature and forest
bathing influence activity in neural structures associated with stress regulation. Additionally,
overall contact with nature seems to help stress reduction and positively correlates with
health benefits (Grinde & Grindal Patil, 2009; Ulrich et al., 1991). However, other variables
Natur’s Effect on Stress Recovery
6
often accompany outdoor nature activities (walking and gardening). Ulrich (1999) mentions
that outdoor social interaction and physical activity impact stress recovery besides nature.
Interpersonal interactions play a part in our well-being. Social interaction with peers, having
good parent-child relationships, and romantic relationships increase the human quality of
life (Peplau, 1994). Wang et al. (2020) have concluded a correlation between higher levels of
social interaction in real-life and lower levels of anxiety and depression. Physical activity
reduces stress and lowers the risks for psychological disorders such as depression. Low-
intensity exercises such as walking immediately lower the levels of the stress hormone
cortisol (Matzer et al., 2017). Additionally, sometimes people prefer to listen to music while
walking. Music has also been widely used as a stress recovery intervention and has been
shown to impact physiological biomarkers and reduce stress in acute psychological stressful
moments (Mitsui Wong et al., 2021).
Studies on the treatment of Shirin-yoku combine low-intensity walking and group
activity (Morita et al., 2007; Park et al., 2009). These activities have been shown to improve
well-being and reduce stress. Consequently, it is challenging for Shirin-yoku research to
conclude nature's effect on stress recovery.
Accordingly, the current study will address whether attendance in nature benefits
stress recovery by controlling the mentioned influential factors. The study will compare the
stress reduction in subjects after walks in natural environments with subjects after walks in
city environments. The current research will measure the physiological and psychological
components of stress. Heart rate variability (HRV) will measure the physiological component
of stress. Karolinska exhaustion disorder scale (KEDS) will measure the psychological
component by assessing exhaustion disorder (ED). The current study selected KEDS to give
an insight into the effect of walks in nature on prolonged stress symptoms. The
measurements will be taken before and after the treatments.
Method
Participants
Twelve participants between the ages of 18 to 35 participated in this study. The
participants had a full-time occupation in the form of being a student or having job
employment, with no ongoing physical or psychiatric disorder, and no participant took
regular walks in nature. Each participant was given an information sheet and a consent form
before participating in the experiment to provide written informed consent. The experiment
has been conducted in line with the declaration of Helsinki. Participants who will score below
two on KEDS will be excluded, as well as participants with uncompleted or missing HRV data
Natur’s Effect on Stress Recovery
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Design
The current study is designed in a between-subject design. Two groups will be
assigned two conditions. The treatment group will take walks in natural environments, and
the control group will take walks in city environments. The natural environment in this study
refers to domains of greenery (forest and green fields) and blue places (ocean, rivers, and
lakes) (Chen & Nagawga, 2019). The groups will be matched and counterbalanced by age,
gender, and stress levels conducted by KEDS. Other variables that may interfere with the
result of the study were also controlled during the failed experiment. Participants were
required to not listen to music, not socialize with a walking partner, and were not allowed to
use their phones for entertainment. To control physical activity, they were informed to be
moderately active throughout their time in the assigned environment. They were allowed to
sit or stand still if they wanted.
The participants were asked to take 30 minutes walks. The walks that assessed stress
recovery in previous studies stretched between 20 to 90 minutes (Park et al., 2007; Bratman
et al., 2015). Accordingly, the current experiment chose 30 minutes walks. It is both
maintainable and effective.
The independent variable is the environmental setting (city or nature), measured in
minutes from the start of each walk. The dependent variables are stress recovery measured
by KEDS score and RMSSD before and after the experiment.
Materials
This study used the Karolinska exhaustion disorder scale (KEDS) to measure stress by
measuring ED symptoms. KEDS is nine questions that measure long-lasting stress symptoms
leading to exhaustion disorder. The scores range from 0 to 54. A score of 18 is considered at
risk for exhaustion disorder. According to the distribution of scores in the KEDS evaluation
study, about 20% scored below 2. (Beser et al., 2014). To ensure the possibility of significant
stress recovery, participants with a score below two were excluded. The KEDS evaluation
article was used to analyze the result (Beser et al., 2014). The questionnaire was answered on
a statistical software (formfacade.com), which also generated the total score for each
participant. The participants answered the questionnaire before starting the experiment,
Additionally, Firstbeat Lifestyle Assessment devices (Bodyguard 2), and a Firstbeat
analysis server was used (Firstbeat is a company that provides analytic technology in sports
and well-being). The technology of the Firstbeat devices monitors heartbeats and measures
HRV by changes in the autonomic nervous system flexibly and over a long period.
The device includes two ends that will be placed on the body with the help of ECG
electrodes. One electrode is placed under the right collarbone and the other on the left side of
Natur’s Effect on Stress Recovery
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the ribs. When the device is set, it will start measuring beat by beat and the variation in time
between each beat. The data measurements will then be exported to the Firstbeat analysis
server. It will provide a report of several variables according to the HRV such as sleep quality,
trying effect, stress, and recovery. Monitoring the function of the autonomic nervous system
related to the heart can help us assess factors of our health, especially stress (Firstbeat
Technologies Ltd., 2014).
Procedure
The first step is for the participants to complete KEDS, which was sent using a google
form to each subject. After all needed information was collected, the subjects were divided
into two groups and assigned a walking environment. All the participants received an
envelope containing an HRV device, eight electrodes (2 will be used at a time and four extras
if needed), an identification code, and printed instructions on using the device. Before
starting the measurements, each participant received a mail from Firstbeat Lifestyle
Assessment to provide some demographical answers and measurements. The participants
also filled in a diary of the measurement days.
Later, all participants were instructed to put on the HRV devices and leave them on
for 24 hours. Twenty-four hours of HRV monitoring were selected according to Firstbeat
Technologies Ltd's (2014) recommendation for assessing stress and recovery. The following
week they took two 30 minutes walks. After each walk, they were instructed to provide a
picture of the setting. A photo will prove they took a walk and that it was in the right
environment. At the end of the week, all participants are required to complete KEDS a second
time and measure HRV for another 24 hours. When finishing the measurement, they will
inform the researcher and return the HRV device and unused electrodes.
Results
A result for KEDS data and the RMSSD data from HRV is presented to determine
whether there is a statistically significant difference in stress post walks in nature compared
to post walks in a city environment. The current study tested 12 participants for the
experiment, six males and six females. Two out of 12 participants were later excluded (one
from each group) due to incomplete HRV data. The exclusion resulted in 10 participants
equally divided, three males and two females in each group. The nature group (GroupN) ages
ranged from 22 to 25 years old, M=23.2 years. The city group (GroupC) ages ranged from 21
to 23 years old, M=22 years.
The several data collection resulted in four datasets for each measurement. Pre walks
in nature (NPre), post walks in nature (NPost), pre walks in a city environment (CPost), and
post walks in a city environment (PostC)
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Descriptive Statics for KEDS Data Sets
KEDS scores were summed into a total score for each participant. Boxplots were
provided for primary screening of the data. The boxplot of CPre shows one outlier and no
whiskers, suggesting the data spread to be concentrated between values 18-19. See figure 1.
The interquartile range (IQR) and the median were provided to understand KEDS
data sets better. See table 1. IQR is highest in NPre, 15.00(14.00), and lowest in CPre,
18.00(1.00). NPost, 11.00(10.00) and CPost, 12.00(8.00)
Figure 1
KEDS Scores Distribution in Boxplots
Note. Boxplots show KEDS data spread pre- and post-walks in nature and city environments. According to the
boxplot, Cpre has one outlier and no whiskers.
Table 1
Descriptive Statistics of KEDS
NPre
Valid
5
Median
15.000
IQR
14.000
NPost
5
11.000
10.000
CPre
5
18.000
1.000
CPost
5
12.000
8.000
Note. This table showes the median and IQR of KEDS scores pre- and post-walks.
Natur’s Effect on Stress Recovery
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Descriptive Statics for RMSSD Data Sets
The result from HRV provided two average RMSSD scores per day of measurement.
One being for awake time and one for sleeping time. The average RMSSD score for each day
was calculated for all participants. For primary data screening, distribution plots were
presented showing the data's frequency and values. See figure 2. Furthermore, the current
study provided the central tendency of the data sets. See table 2. NPre, (M= 31.900, SD=
12.142 ); NPost, (M= 30.000, SD= 12.986); CPre, (M= 50.000, SD= 18.765); CPost, (M=
43.700, SD= 14.215).
Figure 2
Distribution plots of RMSSD
Note. Distribution plots showing the distribution for the RMSSD scores obtained from HRV measurements, pre-
and post walks.
Table 2
Descriptive Statistics for RMSSD
Valid
Mean
Std. Deviation
NPre
5
31.900
12.142
NPost
5
30.000
12.986
CPre
5
50.000
18.765
CPost
5
43.700
14.215
Note. This table shows the mean and the stander deviation for averaged RMSSD scores, taken from HRV
measurements pre- and post-walks.
Natur’s Effect on Stress Recovery
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Inferential Statistics
Analysis was conducted on the KEDS data and on the RMSSD data to determine
within groups significant differences (CPre with Cpost, NPre with NPost). Additionally, an
analysis was conducted to determine the significant differences in-between GroupN and
GroupC. All test was run as two-tailed tests with an alpha level of 0.05.
KEDS’s Within Group
Shapiro-Wilk test was conducted to test for normality. NPre, P =.756; NPost, P =
.464; CPre, P=.023; CPost, P = .642. According to Shapiro-Wilk CPre is not normally
distributed with a P-value <0.05.
A paired-samples t-test tested GroupN (NPre with NPost). The test presented a mean
difference of 6.400. On average GroupN participants scored 6.4 points less on the second
KEDS measurement after their walks in nature. The t-test indicated a non – significant
difference (t (4) =1.401, P=0.234). Cohen’s d = 0.427, states a medium effect size. The non –
parametric equivalent to the paired-samples t-test, Wilcoxon signed-rank test, was
performed for GroupC (CPre with CPost) (W=15.00, P = 0.063). According to the fowling
formula, the effect size was cucullated: 𝑟 = 𝑧/√𝑛 = (2.023/√10 = 0.63972877065 ≈ 0.64).
The result indicated no significant difference with a medium to large effect size.
RMSSD Within Group
The Shapiro-Wilk test was likewise conducted on RMSSD data sets. NPre, P =0.307;
Npost, P = 0.110, Cpre, 0.207; Cpost, P = 0.983.
Paired samples t-test was conducted on both groups. GroupN (Npre with NPost)
showed no significant difference, (t (4) 0.709, P=0.518) with Cohen’s d = 0.317, which
suggests a small effect size. The mean difference = 1.90, indicates on average participants had
1.90 points higher recovery in NPre, (M=31.900, SD=12.142) than Npost, (M= 30.00, SD=
12.986). GruopC (CPre with CPost) showed no significant difference in stress recovery, (t (4)
2.059 P = 0.109) with Cohen’s d = 0.921 suggesting a large effect size. The mean difference =
6.300, indicating that, on average GroupC had a higher recovery on CPre (M= 50.00 SD=
18.765) by 6.300 points compared to CPost (M=43.700, SD=14.215)
In-Between Group Analysis
To compare KEDS’s data pre-walks in-between the groups (KEDSpre), a Mann –
Whitney test was provided (U=11, P= 0.834) with rB = 0.120, a small effect size. The result
demonstrated no significant difference between the groups. Independent t-test provided a
Natur’s Effect on Stress Recovery
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comparison in-between group, post walks (KEDSpost), (t (8) 0.457, P=0.660), indicating no
significant difference. Cohen’s d = 0.289, which is a small effect size.
Two independent t-tests were provided for RMSSD to compare the groups. RMSSD
result before walks (RMSSDpre) showed (t (8) 1.811, P=0.108) with Cohen’s d = 1.145
indicating a large effect size and non-significant result. RMSSD result post walks
(RMSSDpost) demonstrated (t (8) -1.591, P = 0.150) with Cohen’s d = 1.006 likewise suggests
a large effect size and nonsignificant result.
According to the test analysis above, the null hypothesis cannot be rejected. There is
no statistical significance of stress recovery measured by the KEDS questionnaire and HRV
before and after walks in nature compared to walks in a city environment.
Discussion
The experiment used KEDS and RMSSD to measure stress and stress recovery.
RMSSD was selected as the parameter of stress recovery extracted from HRV. RMSSD is
widely used for Twenty-four-hour measurements and correlates with other parameters in no-
linear indexes, frequency domain parameters, and other time-domain parameters, such as
PNN50. RMSSD is also more sensitive to changes in PNS than other parameters such as
SDNN, making the values of RMSSD a good indicator of stress recovery. Lower RMSSD
values indicate lower recovery, and higher RMSSD values indicate higher recovery (Shaffer &
Ginsberg, 2017).
Findings
The current study found no significant difference in stress recovery before and after
walks in nature compared to walks in city environments.
The in-between group comparison KEDSpre showed no significant difference and a
small effect size between the group's scores. The result of KEDSpre supports the experiment
design, which set out to counterbalance stress levels pre walks according to KEDS between
the groups. However, although the result of RMSSDpre showed no significant difference, it
had a large effect size. RMSSDpre suggests that, on average GroupC had higher levels of
stress recovery than GroupN before the walks.
The result for both KEDSpost and RMSSDpost demonstrated no significant difference
between GroupN and GroupC. However, similarly to the pre walks result RMSSDpost had a
large effect size between GroupN and GroupC. On average GroupC demonstrated higher
levels of stress recovery post walks.
On average, all participants (GroupN and GroupC) scored less on KEDS after the
walks compared to before the walks. Suggesting less experienced ED symptoms. In contrast,
Natur’s Effect on Stress Recovery
13
RMSSD values on average, declined after the walks, indicating less stress recovery and higher
stress levels. The different results are explained by the two measurements testing various
factors. KEDS is an ED measurement measuring ED symptoms over previous two weeks.
Meanwhile, RMSSD measures the average HR changes, indicating stress recovery (Shaffer &
Ginsberg, 2017; Beser et al., 2014).
Limitations and strengths
In future testing of stress recovery Perceived Stress Scale (PSS) may be a better match
for this type of experiment rather than KEDS, which asses a disorder of stress. PSS lets
subjects evaluate to what degree they have perceived factors in their lives to be stressful (Lee,
2012). PSS may give more complementary results between the physiological and the
psychological stress measurements.
More than 24 hours of HRV monitoring should also be considered for future research.
E.g., 72 hours of HRV can give a more averaged stress recovery result of day-to-day life, and
it may also show a significant change in RMSSD.
The current experiment took the second measurements at the end of the experiment
week, expecting that all participants had taken their two walks. Walk number two could have
been taken one to five days before the second measurement. This procedure differs from
previously mentioned studies, where the second measurements were taken immediately after
the nature innervation (Ulrich et al., 1991; Park et al., 2007; Bratman et al., 2005). Delayed
second measurements after the intervention could have impacted the result of the current
experiment. Another limitation is the exclusion of two participants due to incomplete HRV
data. The exclusion further affected the small sample size. Larger sample size could help
identify statistical significance and effect sizes in this experiment. A limitation of the in-
between group comparison is that GroupC had higher levels of stress recovery than GroupN
before the treatment, which was indicated by the large effect size in RMSSDpre. First RMSSD
measurements should have been balanced between the groups, letting only the independent
variable (walking environment) to differ.
On the flip side, the current study did note the importance of alternative interventions
for reducing stress. It gave an insight into how nature interventions may reduce prolonged
stress symptoms in exhaustion disorder. As mentioned earlier in the study, prolonged stress
changes the brain by shrinkage of dendrites in the prefrontal cortex (PFC) and dendritic
expansion in the amygdala. The brain changes lead to poorer executive functions such as
working memory, regulating self-related thoughts (rumination), and goal-directed behavior.
It also contributes to poorer regulation of potential threats and negative emotions (Henckens
et al., 2012; McEwen & Morrison, 2013). Pharmacological interventions, such as serotonin
reuptake inhibition (SSRI), come with many side effects, such as memory loss. Therefore,
Natur’s Effect on Stress Recovery
14
nature-based intervention can improve the lives of many people suffering from prolonged
stress and stress disorders (Mitsui Wong et al., 2021).
The experiment considered limiting factors that may influence the testing of nature's
effect on stress recovery, such as socializing and music (Mitsui Wong et al., 2021; Ulrich,
1999). While previous mentioned studies testing the impact of walks in nature did not control
these factors. The experiment's sample size included an approximately equal ratio of male
and female participants, giving a more varied sample compared to previous studies, which
tested only male subjects (Park et al., 2007; Jones et al., 2021).
Conclusion
The current study measured and compared stress recovery in five treatment
subjects that took two 30 minutes walks in nature and five control subjects that took two 30
minutes walks in a city environment. The experiment could not establish a significant stress
reduction after nature intervention; however, it does not reject nature’s positive impact on
stress recovery. The reductions in KEDS scores after the walks may further facilitate
discussion associated with nature-based interventions and the recovery of stress-related
disorders. Moreover, observed and controlled factors may be impacting the research in this
field. More research needs to be made on nature interventions and stress recovery to establish
a solid scientific evidence-based method for people that suffers from altered cognitive
functions, negative emotions, and fatigue due to stress.
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References
Bratman, G. N., Hamilton, J. P., Hahn, K. S., Daily, G. C., & Gross, J. J. (2015). Nature
experience reduces rumination and subgenual prefrontal cortex activation.
Proceedings of the national academy of sciences 112(28), 8567–8572.
10.1073/pnas.1510459112
Beser, A., Sorjonen, K., Wahelberg, k., Peterson U., Nygre, Å., & Åsberg, M. (2014).
Construction and evaluation of a self rating scale for stress-induced Exhaustion
Disorder, the Karolinska Exhaustion Disorder Scale. Scandinavian Journal of
Psychology 55(1), 72-82. 10.1111/sjop.12088
Cartwright, M. (27 July 2018). Hanging Gardens of Babylon. World History Encyclopedia.
https://www.worldhistory.org/Hanging_Gardens_of_Babylon/
Chen, C., & Nagawga, S. (2019). Nature's pathways on human health. Kotte, D., Li, Q., Shin,
W. S., Michalsen, A (Eds.), International Handbook of Forest Therapy (pp.12-31).
Newcastle upon Tyne, UK: Cambridge Scholars Publishing.
Croswell, D. A., & Lockwood, G. K. (2020). Best practices for stress measurement: How to
measure psychological stress in health research. Health Phsychology Open 7(2),
2055102920933072. 10.1177/2055102920933072
Corazon, S. S., Sidenius, U., Poulsen, D. V., Gramkow, M. C., & Stigsdotter, U. K. (2019).
Psycho-Physiological Stress Recovery in Outdoor Nature-Based Interventions: A
Systematic Review of the Past Eight Years of Research. International journal of
environmental research and public health, 16(10), 1711. 10.3390/ijerph16101711
Firstbeat Technologies Ltd. (2014). Stress and Recovery Analysis Method Based on 24-hour
Heart Rate Variability [White Paper]
https://assets.firstbeat.com/firstbeat/uploads/2015/10/Stress-and-recovery_white-
paper_20145.pdf
Gazzaniga, M. S. (2016). Psychological Science (international student edition, Vol. 6).
Norton.
Grinde, B., & Patil, G. G. (2009). Biophilia: Does Visual Contact with Nature Impact on
Health and Well-Being? International Journal of Environmental Research and
Public Health 6(9), 2332-2343. 10.3390/ijerph6092332
Henckens, M. J. A. G., van Wingen, G. A., Joëls, M., & Fernández, G. (2012). Time-dependent
effects of cortisol on selective attention and emotional interference: a functional MRI
study. Frontiers in Integrative Neuroscience, 6. 10.3389/fnint.2012.00066
Jones, R., Tarter, R., & Ross, A. M. (2021). Greenspace Interventions, Stress and Cortisol: A
Scoping Review. International journal of environmental research and public health
18(6), Article 2802. 10.3390/ijerph18062802
Natur’s Effect on Stress Recovery
16
Kubokawa, K., Watanabe, T., Yoshioka, M., & Iwata, M. (1999). Effects of acute stress on
plasma cortisol, sex steroid hormone and glucose levels in male and female sockeye
salmon during the breeding season. Aquaculture, 172(3–4), 335–349.
10.1016/S0044-8486(98)00504-3
Lederborgen, F., Kirsch, P., Haddad. L., Streit, F., Tost, H., Schuch, P., Wu ̈st, S., Pruessner,
J. C., Rietschel, M., Deuschle, M., & Lindenberg, A. M. (2011). City living and urban
upbringing affect neural social stress processing in humans. Nature 474(7352), 498–
501. 10.1038/nature10190
Lee, E. H. (2012). Review of the Psychometric Evidence of the Perceived Stress Scale. Asian
Nursing Research, 6(4), 121–127. https://doi.org/10.1016/j.anr.2012.08.004
Matzer, F., Nagele, E., Lerch, N., Vajda, C., & Fazekas, C. (2017). Combining walking and
relaxation for Stress reduction—A randomized crossover trial in healthy adults. Stress
and Health 34(2) 266-277. 10.1002/smi.2781
McEwen, B., & Morrison, J. (2013). The Brain on Stress: Vulnerability and Plasticity of the
Prefrontal Cortex over the Life Course. Neuron, 79(1), 16–29.
10.1016/j.neuron.2013.06.028
Morita, E., Fukuda, S., Nagano, J., Hamajima, N.,Yamamoto, Y., Iwai, Y., Nakashima, T.,
Ohira, H., & Shirakawa, T. (2007). Psychological effects of forest environments on
healthy adults: Shinrin-yoku (forest-air bathing, walking) as a possible method of
stress reduction. Public Health 121(2) 54–63. 10.1016/j.puhe.2006.05.024
Park, B. J., Tsunetsugu, Y., Kasetani, T., Hirano, H., Kagawa, T., Sato, M., & Miyazaki,
Y.(2007). Physiological Effects of Shinrin-yoku (Taking in the Atmosphere of the
Forest) Using Salivary Cortisol and Cerebral Activity as Indicators. J Physiol
Anthropol, 26(2), 123–128. 10.2114/jpa2.26.123
Park, B.J., Tsunetsugu, Y., Kasetani, T., Kagawa, T., & Miyazaki, Y. (2009). The physiological
effects of Shinrin-yoku (taking in the forest atmosphere or forest bathing): evidence
from field experiments in 24 forests across Japan. Environ Health Prev Med 15(1),
Article 18. 10.1007/s12199-009-0086-9
Park, S., Song, C., Oh, Y. A., Miyazaki, Y., & Son, K. C. (2017). Comparison of physiological
and psychological relaxation using measurements of heart rate variability, prefrontal
cortex activity, and subjective indexes after completing tasks with and without foliage
plants. International journal of environmental research and public health 14(9),
Article 1087. 10.3390/ijerph14091087
Peplau, E. H. (1994). Quality of Life: An Interpersonal Perspective. Quality of Life: An
Interpersonal Perspective. Nursing Science Quarterly 7(1), 10-15.
doi.org/10.1177/089431849400700107
Natur’s Effect on Stress Recovery
17
Shaffer, F., & Ginsberg, J. P. (2017) An Overview of Heart Rate variability Metrics and Norms.
Front. Public Health 5, article 258. 10.3389/fpubh.2017.00258
Thayer, J. F., Åhs, F., Fredrikson, M., Sollers, J. J., & Wager, T. D. (2012). A meta-analysis of
heart rate variability and neuroimaging studies: Implications for heart rate variability
as a marker of stress and health. Neuroscience & Biobehavioral Reviews, 36(2), 747–
756. 10.1016/j.neubiorev.2011.11.009
Ulrich, R. S. (1999) Effects of gardens on health outcomes: Theory and research. In C. C.
Marcus, And M. Barnes (Eds.) Healing Gardens. Therapeutic Benefits and Design (pp.
27–87) New York: Whiley.
Ulrich, R. S., Simnos, R. F., Losito, B. D., Fiorito, E., Miles, M. A., & Zelson, M. (1991). Stress
recovery during exposure to natural and urban environments. Journal of
Environmental Psychology 11(3), 201-230. 10.1016/S0272-4944(05)80184-7
Wang, P., Lin, P., Lin, C., Yang, S., & Chem, K. (2020). Does Interpersonal Interaction Really
Improve Emotion, Sleep Quality, and Self-Efficacy among Junior College Students?
Environmental Research and Public Health 17(12), Article 4542.
10.3390/ijerph17124542
Wilson, E. O. (1984). Biophilia (Revised ed., Vol. 1). Harvard University Press.
Wong, M. M., Tahir, T., Wong, M. M., Baron, A., & Finnerty, R. (2021). Biomarkers of Stress
in Music Interventions: A Systematic Review. Journal of Music Therapy, 58(3), 241–
277. 10.1093/jmt/thab003