Sage Journals: Discover world-class research

Abstract

Background

The effect of a forest therapy in a natural environment noted that the forest therapy induced a state of relaxation among workers, thereby decreasing cortisol levels and work-related stress.

Objective

The primary objective of this study is to determine the effects of the forest therapy for employees in the manufacturing industry on psychological stress responds, stress hormone and heart rate variability (HRV). The secondary objective is to determine the effects of the forest therapy for employees in the manufacturing industry on cytotoxic activity of natural killer (NK) cells, health-related quality of life and mood states compare to urban untreated and remained in urban environment.

Methods

Forty-two employees were recruited from a single workplace located in Incheon city, Republic of Korea. Participants were allocated to either an experimental group (n= 21), wherein they participated in the forest therapy and or a control group (n= 21), wherein they were given no treatment. Participants were assigned to these groups on a randomized, open-label basis. Pre and post-test measures of natural killer (NK) cell activity, salivary cortisol, heart rate variability (HRV), health-related quality of life, stress response, and mood states were taken for both groups.

Results

The results showed that participants who took part in the forest therapy showed greater physiological improvement when compared to those in the control group, as indicated by a significant increase in some HRV measures. The forest therapy also contributed to a significantly greater decrease in work-related stress symptoms and a significantly greater improvement in health-related quality of life and mood states compared to participants in the control group.

Conclusions

These results may suggest that the forest therapy could be an effective means of relaxation technique, reducing stress and leads to an increase in positive mood for employees in the manufacturing industry.

Keywords

stress stress management forest therapy salivary cortisol natural killer cell activity heart rate variability

Introduction

According to the statistics from the Organization for Economic Co-operation and Development (OECD), the Republic of Korea had the second-longest working hours among OECD nations in 2021.¹ More than two-thirds of Korean adults responded that they are under stress in their work environment and approximately 20% of these reported that they are under constant stress. Around 25% of workers in Korea have been categorized as a high-risk group in terms of work-related stress.²

The stress of workers can be defined as deleterious physical and emotional responses arising when job requirements are inconsistent with workers' ability, resources, and desires.³ The stress of workers is a complex phenomenon caused by various factors within the modern industrial structure. It can lead to exhaustion and declines in physiological function and work efficiency. From an occupational health perspective, the stress of workers can be defined as fatigue caused by excessive mental and physical labour.² Such a state of fatigue tends to result in reduction or loss of functioning.⁴ Work-related stress can have a significant negative impact on workers’ health and quality of life, which, in turn, can put a heavy burden on society, causing increased utilization of medical services and rates of industrial accidents.⁵ In manufacturing industries, environmental factors such as noise, unpleasant odours, vibrations and high density of workers are associated with stress.⁶ In addition, electric cables, wires and mechanical machines at the workplace scenery is a considerable cause of work stress.⁷

From a health perspective, stress can cause depression and neurological disorders and has been reported to have a direct impact on various physical illnesses, including hypertension and coronary artery disease.⁸ It has also been reported that long-term exposure to stress can result in decreases in immune competence.⁹ Efforts to ensure the effective management of stress are needed not only to improve individual worker’s health but also to manage the work environment to be healthy and productive.

According to studies which investigated the effects of mindfulness-based interventions and mindfulness-based stress reduction (MBSR) and for work-related stress in various occupations and industrial sectors, these interventions were able to decrease work-related stress and nurture individuals’ ability to cope with stress effectively.^10-12 A study has also demonstrated that exposure to nature sound was reported to facilitate recovery from sympathetic activation.¹³ Although individual stress management strategies appear to be effective in reducing stress, a multidisciplinary approach may be more effective than any single strategy on its own.¹⁴

A notable intervention for alleviating work-related stress is the presence of a natural or forest environment, which is highly correlated with the quality of life.¹⁵ There are numbers of studies in which reports ranges of health benefits through either visiting or participating therapeutic activities in the forest environments.^16-18 Studies have reported that the natural environment exerts positive effects on workers’ productivity, including reducing the frequency of absence without leave and improving their motivation to work.^19,20 Greenery and plants in the workplace reported as contributing factors improving the quality of the workplace environment and maintaining positive emotional states.²¹ Moreover, it was reported that employees working in environments with accesses to nature had lower work-related stress and higher job satisfaction compared to those working in environments without nature access.²² In studies wherein the differences in the effects of exercise conducted in urban and natural environments were examined in detail, it was reported that stress decreased when exercise was conducted in a natural environment, as this led to activation of the parasympathetic nerve functions, which in turn caused a physical relaxation effect.²³

Similarly, when researchers compared the effects of walking in natural environments (including natural environments within urban environments) and urban environments, stress and negative mood states were identified to decrease more after walking in natural environments as compared to urban environments. A study on the effect of a forest therapy in a natural environment noted that the forest therapy induced a state of relaxation among workers, thereby decreasing cortisol levels and work-related stress.²⁴ A study has reported that a significant reduction in blood pressure and contributed positive mood state via the forest therapy on adult population.²⁵

Thus, the primary objective of this study is to determine the effects of the forest therapy for employees in the manufacturing industry on psychological stress responds, stress hormone and heart rate variability (HRV). The secondary objective is to determine the effects of the forest therapy for employees in the manufacturing industry on cytotoxic activity of natural killer (NK) cells, health-related quality of life and mood states compare to urban untreated and remained in urban environment.

Materials and Methods

Sample Size Calculation

A sample size calculation was carried out prior to conducting this research. The sample size calculation, based on ANOVA result, effect size (f = .070), and a power of 80% was conducted by using G^*Power version 3.1.9.7 (Universität Düsseldorf).²⁶ The estimated sample size was calculated to be 42 participants.

Participants and Design

The study participants were full-time employees from a public-sector manufacturing company located within the industrial area of Incheon city, Republic of Korea. Overall, 65 participants took part in screening conducted from June to September, 2014. This initial survey involved ensuring that participants were willing to participate in the study, and confirming that they met the inclusion and exclusion criteria. Inclusion criteria were (a) being adult (between 18 and 65 years), (b) in active employment in manufacturing industry. In contrast, exclusion criteria were (a) concurrent psychiatric illnesses, being a frequent user of natural environments (visiting more than 3 times a week), (b) taking medications including hypertensive, diabetes, and pain relievers, including oral hormone/corticosteroid drugs) and (c) history of outdoor allergens in which allergic disease can exacerbate of psychological stress and discomfort.²⁷

Forty-three subjects satisfied the inclusion criteria and agreed to take part in the 3 consecutive days of the experiment. Participants were randomly assigned to either the experimental or an active control group using a random number table. Specifically, a random number generator was used to create a list of random numbers from a minimum value of 1 to a maximum value of 43. Odd numbers were assigned to the experimental group and even numbers to the control group. Out of the 43 eligible participants, a participant dropped out of the study due to a personal problem after the screening test. In total, 21 participants respectively were allocated to the experimental group (received the forest therapy) and active control group (remained in urban environment) as shown in Figure 1.

Figure 1.

CONSORT flow diagram of the study participants.

The purposes, procedures, and possible hazards of the experiment were explained to the participants, and they were free to leave the experiment at any time. All of the participants were asked to sign a written informed consent form before entering the experiment. Comparable data were retrieved from the active control group on October, 2014. An identical set of measurements and procedures was administered to both groups. This study received ethical approval from the Institutional Review Board of Seoul Paik Hospital [IIT-2014-166].

Demographic characteristics in the experimental and control groups are shown in Table 1. The demographic characteristics of participants were analyzed using chi-square and independent sample t-tests to compare variances for the groups and differences between groups at baseline in order to verify their heterogeneity. There were no significant differences between the 2 groups (P> .05).

Table 1.

Demographic characteristics of the experimental and control groups.

Factors	Sub-Factors	Experimental Group (n = 21)	Control Group (n = 21)	χ2 or t	p
Factors	Sub-Factors	N (%) or M(SD)	N (%) or M(SD)	χ2 or t	p
Gender	Male	21 (100)	21 (100)	—
Gender	Female	0 (0)	0 (0)	—
Age	—	43.52 (7.33)	45.86 (8.20)	.972	.337
Ethnicity	Korean	21 (100)	21 (100)	—
Education Level	College degree	11 (52.38)	14 (66.67%)	1.893	.388
	Undergraduate degree	8 (38.10%)	4 (19.05%)
	Postgraduate degree	2 (9.52%)	3 (14.29%)
Length of employment (years)	—	12.38 (7.46)	13.76 (5.96)	.663	.511

Experimental Treatment

The forest therapy was conducted on September 25-27, 2014, in Saneum Natural Recreation Forest, which is situated in Yangpyeong County of Gyeonggi Province, Republic of Korea. The Saneum Natural Recreational Forest, total area of 2,140 hectare, is an inland mountain forest, mainly composed of conifers and natural broadleaf trees from temperate regions. The forest therapy was adapted from an evidence-based intervention that has proven effective for reducing the work-related stress of female employees of the healthcare and counselling service industries.²⁴ The activities were conducted and assessed by a team of professionals, including a psychiatrist, a forest therapist and an art therapist. The weather on the days of the experiment was sunny, and the average temperature was 19.9 Celsius (°C), minimum temperature: 15.2°C, maximum temperature: 25.2°C with 82.4% humidity, average wind speed of 1.0 m per second, and an average sunshine duration of 6.9 hours.

Primary Assessments

Worker’s Stress Response Inventory Modified Form (WSRI-MF).²⁸ is a self-report questionnaire adapted from the Stress Response Inventory-Modified Form (SRI-MF).²⁹ specifically, it contains 4 additional work-related items, for a total of 22 items in 3 subscales; depression, somatization, anger. Each item is rated on a five-point Likert scale and internal reliability was .94.²⁸

Cortisol level was measured by collecting saliva in Salivettes® tubes (Sarstedt AG and Co., Germany); the tubes were kept at room temperature until they were delivered to Meditree co. Ltd (Seoul, Republic of Korea) for cortisol analysis according to the manufacturer’s methods. Pre- and post-test saliva samples were collected in the morning as baseline due to salivary cortisol levels are highly sensitive to time of day, especially in the morning.³⁰

Heart rate variability (HRV) was used to determine the effects of sympathetic nervous system stimulation. A long-term R-R interval (RRI) T-REX® (Monitor and Care Taewoong Medical, Gyeonggi Province, Republic of Korea) recorder and Y-shaped customized electrocardiography electrode were fitted to the participant’s chest area to measure HRV.

Secondary Assements

Cytotoxic activity of natural killer (NK) cells was determined using the NK Vue-Kit® (ATgen, Sungnam, Republic of Korea). 10 mL of blood was collected by using BD Vacutainer® heparin N1 tubes, and then incubated 1 mL of whole blood for 24 hours at 37°C under 5% CO2 with an indicated dose of Promoca® and 1 mL of RPMI 1640 medium. Cell-free supernatants were harvested, and NK cell activity levels were determined according to the manufacturer’s protocols.

The EuroQol Visual Analog Scale (EQ-VAS) is an instrument for assessing health-related quality of life. We assessed participants’ health-related quality of life with a score range of 0, indicating the worst imaginable health state, to 100, indicating the best imaginable health state.³¹

The Profile of Mood States (POMS) identifies and assesses transient, fluctuating moods. The POMS measures 6 identifiable mood or affective states; tension–anxiety, vigour–activity, depression–dejection, fatigue–inertia, anger–hostility, and confusion–bewilderment. In this study, the POMS was used to detect participants’ mood responses to the current situation and assess acute treatment effects.³²

Procedure

Among all participants, alcohol consumption, exercise, and visits to a natural environment were prohibited 8 hours before the beginning of the pre-test, and smoking and intake of food, including caffeinated beverages, were prohibited 1 hour before the tests. As a contributing variable, participants were asked to avoid alcohol and personal exercise routine. The first day started with pre-test measurements at a hospital in an urban environment. After taking saliva samples, HRV recorders were fitted to participants, and then they completed the psychological instruments and a questionnaire on demographic information. Blood samples were then collected for measurement of NK cell activity. After blood samples were collected, participants took a break for 10 minutes to adjust to the new environment and the HRV recorder. Participants then sat on chairs for half an hour in order to collect baseline HRV data. Participants did not speak to each other during this time and were asked not to close their eyes or fall asleep. Subsequently, the experimental group was driven 2 hours to the experiment site, at which point the forest therapy commenced with walking and outdoor activities in the forest environment. Participants stayed the night at a lodge in the Saneum Natural Recreation Forest. On the second day, they participated in mindfulness-based meditation. On the third day, the program ended with post-test measurements, which followed an identical sequence to the pre-test at a hospital in an urban environment. A detailed description of the mindfulness component is as following. At the beginning of forest walking, the participants were guided to slow down their pace and drive their attention to the contact with the ground, our mother nature. To improve the quality of mindfulness, we helped the participants to focus their awareness to the present moment and become aware of their feelings, thoughts, and bodily sensations. We helped them to be tuned all their senses of the sights, sounds, olfaction, tastes, and textures with the forest environment. For example, the participants had a chance to lie down and slowly observe the specific parts of trees from beneath which can help them to step back and see something from a different perspective. They also practiced deep breathing and feel the sensations from their nostrils and smell the fragrance of woods. Participants learned to notice the various sounds from the forest, such as the sounds of birds and streams, and feel the emotional and physiological changes. Barefoot walking and embracing the trees were performed to awake their tactile sensation. We also helped the participants to become aware of their inner state of mind to cultivate the profound quality of mindfulness. See Table 2 for a detailed overview of the forest therapy. In contrast, participants in the control group visited the hospital for pre and post-testing, which followed an identical protocol to the experimental group. The experimental group remain in the urban environment. During the study period, participants in the control group stayed in hotel and were controlled from taking part in therapeutic activities, visiting natural environments or urban parks. Furthermore, among all participants, work and exercise and social gathering were controlled other than list of activities shown in Table 2. Participant’s preference for specific relaxation modalities and the stress management methods were not surveyed.

Table 2.

Overview of the experiment procedures and the schedule.

Time	Experimental Group		Control Group
Time	Events	Location	Events	Location
Day 1	—
09:00-10:30	Pre-test	Urban environment	Pre-test	Urban environment
14:30-16:30	Walk in the forest	Natural environment	Walk in the city	Urban environment
Day 2	—
09:30-10:30	Walk in the forest	Natural environment (indoor)	Walk in the city	Urban environment (indoor)
10:30-12:30	Mindfulness-based meditation		Mindfulness-based meditation
14:00-17:00	Mandala coloring		Mandala coloring
Day 3	—
09:00-10:30	Post-test	Urban environment	Post-test	Urban environment

Statistical Analyses

All statistical analyses were performed using SPSS Statistics 21.0 (IBM Corp. Armonk, NY, USA). Since HRV were skewed (and therefore not normally distributed), log-transformation was conducted on the following HRV indices: heart rate (HR), standard deviation of all NN intervals (SDNN), the square root of the mean sum of squares of differences between adjacent NN intervals (RMSSD), total power (TP), and the ratio of power in the low-frequency range to power in the high-frequency range (hereafter, “ratio”). The demographic data of participants were analyzed using chi-square and independent sample t-tests to compare variances for the groups and differences between groups at baseline. Differences between 2 groups were analyzed by conducting Repeated Measures ANOVA with the time of measurement (pre, post) as a within factor and group (experimental, control) as a between-subjects factor. Post-hoc analyses of the differences between pre- and post-test measurements within groups were analyzed with paired sample t-tests. If variables had significantly different baselines, they were included as covariates in an analysis of covariance (ANCOVA) to determine their possible influence on the other variables.

Results

Physiological Assesement

To compare the homogeneity of variance between the experimental and control groups, an independent sample t-test was used. The result identified a significant difference in the pre-test NK cell activity between the 2 groups (t= −2.720, df= 38, P = .010). Thus, an ANCOVA was conducted to control for pre-test NK cell activity. No significant difference in NK cell activity measured at post-test was observed between the 2 groups (f= .032, P = .859).

To compare changes in salivary cortisol concentration and HRV indices between the experimental and control groups, repeated measures ANOVA was conducted. The results indicated no significant difference in the change in cortisol between the 2 groups (f = .092, P = .763). However, significant differences were observed between 2 groups in terms of the differences between pre- and post-test measurements of HRV: HR (f= 8.114, P = .007, $η$ _p²= .176), SDNN (f= 8.753, P = .005, $η$ _p²= .187), RMSSD (f= 13.000, P = .001, $η$ _p²= .255), TP (f= 5.071, P = .030, $η$ _p²= .118), ratio (f= 15.785, P = .001, $η$ _p²= .293), low-frequency power in normalized units (f= 24.205, P = .001, $η$ _p²= .389), and high-frequency power in normalized units (f= 24.205, P = .001, $η$ _p²= .389).

A paired sample t-test was used to verify the changes in pre- and post-test physiological variables within each group. The results are shown in Table 3. The incline in NK cell activity was significant only within the experimental group (t = 2.695, df= 20, P = .014). Moreover, salivary cortisol declined significantly within the experimental group (t= −2.333, df= 20, P = .030), while the decline in salivary cortisol was not significantly within the control group (t= −.791, df= 20, P = .438). The differences in HRV indices within each group were also examined. The results identified that mean HR (t= 4.244, df= 20, P = .001), SDNN (t= 3.981, df= 20, P = .001), RMSSD (t= 4.168, df= 20, P = .001), TP (t= 3.344, df= 20, P = .003), and HF norm (t= 4.967, df= 20, P = .001) increased in the experimental group. High RMSSD value indicates low stress and LF demonstrates both sympathetic and vagal activation. HF component is synchronous with respiration and is modulated by the vagal tone.³⁸ High LF indicates high stress and high HF indicates low stress. However, there were no differences in the control group. Both the LF/HF ratio (t= −3.928, df= 20, P = .001) and LF norm (t= −4.967, df= 20, P = .001) decreased in the experimental group; in contrast, there were no differences in the control group in these 2 indices (P > .05).

Table 3.

Comparison of physiological measurements between pre- and post-test within experimental and control groups.

Variables	Sub-Factors	Group	M(SD)		t	p	d
Variables	Sub-Factors	Group	Post	Pre	t	p	d
NK cell		Experimental	306.79 (255.26)	231.25 (180.55)	2.695^*	.014	.59
NK cell		Control	481.80 (264.74)	433.15 (282.49)	.931	.364	.21
Cortisol		Experimental	.41 (.11)	.48 (.16)	−2.333^*	.030	.51
Cortisol		Control	.52 (.26)	.57 (.29)	−.791	.438	.17
HRV	HR‡	Experimental	1.95 (.06)	1.88 (.08)	4.244^***	.001	.93
	HR‡	Control	1.93 (.06)	1.92 (.07)	.805	.431	.18
	SDNN‡	Experimental	2.01 (.26)	1.82 (.23)	3.981^**	.001	.87
	SDNN‡	Control	1.92 (.36)	1.94 (.35)	−.323	.751	.07
	RMSSD‡	Experimental	1.93 (.48)	1.62 (.42)	4.168^***	.001	.91
	RMSSD‡	Control	1.71 (.58)	1.76 (.59)	−.758	.458	.17
	TP‡	Experimental	3.89 (.47)	3.59 (.43)	3.344^**	.003	.73
	TP‡	Control	3.75 (.66)	3.76 (.59)	−.036	.972	.01
	LF/HF Ratio‡	Experimental	.11 (.45)	.37 (.39)	−3.928^**	.001	.86
	LF/HF Ratio‡	Control	.37 (.52)	.25 (.53)	1.756	.096	.40
	LF norm	Experimental	50.91 (19.28)	64.42 (17.63)	−4.967^***	.001	1.08
	LF norm	Control	64.72 (22.97)	59.25 (24.07)	2.010	.060	.46
	HF norm	Experimental	49.09 (19.28)	35.58 (17.63)	4.967^***	.001	1.08
	HF norm	Control	35.28 (22.97)	40.75 (24.07)	−2.010	.060	.46

Note: NK cell: natural killer cell, HRV: heart rate variability, HR: heart rate, SDNN: standard deviation of all NN intervals, RMSSD: the square root of the mean of the sum of the squares of differences between adjacent NN intervals, TP: total power (variance of all NN intervals), Ratio: ratio LF (power in low frequency range)/HF (power in high frequency range), LF norm: LF power in normalized units, HF norm: HF power in normalized units, * P < .05, ** P < .01, *** P < .001. ‡ log-transformed values.

Psychological Assesement

First, an independent sample t-test was conducted in order to test the homogeneity between groups in their pre-test stress scores; however, there was no statistically significant difference. Repeated measures ANOVA and paired sample t-tests were then conducted to identify whether the forest therapy had an effect on changes in stress responses. The results of repeated measures ANOVA were statistically significant differences between the groups in terms of changes in the following sub-factors of stress: somatization (f= 12.638, P = .001, $η$ _p²= .240), depression (f= 12.602, P = .001, $η$ _p²= .240), anger (f= 12.702, P = .001, $η$ _p²= .241), work-related symptoms (f = 24.634, P = .001, $η$ _p²= .381), and total stress score (f= 22.131, P = .001, $η$ _p²= .356). The lower-order subscales of work-related symptoms also reported significant differences between groups: lack of motivation (f= 22.085, P = .001, $η$ _p²= .356), leave of absence (f= 4.211, P = .047, $η$ _p²= .095), and lack of concentration (f= 6.480, P = .015, $η$ _p²= .139). Turnover intention was not significantly different between the experimental group and the control group (f= 2.530, P = .120, $η$ _p²= .059).

The results of the paired sample t-test are shown in Table 4. After participation in forest therapy, the WSRI total and subscale scores all tended to decrease in the experimental group, and these changes were statistically significant. In contrast, although the control group showed an increasing tendency for all such scores, the changes were not statistically significant. When comparing the changes between the groups, lack of motivation and turnover intention tended to decrease in both groups. However, only in the experimental group was the decrement in lack of motivation significant (t= −5.595, df= 20, P = .001). Furthermore, leave of absence and lack of concentration significantly decreased in the experimental group (t= −2.609, df= 20, P = .017).

Table 4.

Comparison of WSRI between pre- and post-test within experimental and control groups.

Variables	Sub-Factors	Group	M(SD)		t	p	d
Variables	Sub-Factors	Group	Post	Pre	t	p	d
WSRI	Somatization Symptoms	Experimental	4.29 (4.14)	9.81 (7.03)	−4.557^***	.001	.99
	Somatization Symptoms	Control	7.95 (8.46)	7.19 (7.39)	.592	.561	.13
	Depressive Symptoms	Experimental	3.24 (3.18)	7.48 (5.17)	−4.377^***	.001	.96
	Depressive Symptoms	Control	5.48 (4.39)	4.90 (4.69)	.603	.553	.13
	Anger Symptoms	Experimental	3.43 (4.51)	7.76 (5.28)	−4.320^***	.001	.94
	Anger Symptoms	Control	6.33 (5.44)	6.24 (5.23)	.130	.898	.03
	Work-related Symptoms	Experimental	1.90 (1.09)	4.19 (2.60)	−4.824^***	.001	1.05
	Work-related Symptoms	Control	3.48 (2.69)	3.14 (2.24)	1.435	.167	.31
	Total	Experimental	12.86 (10.75)	29.24 (16.66)	−6.023^***	.001	1.31
	Total	Control	23.24 (18.89)	21.48 (17.94)	.644	.527	.14

Note: WSRI: worker’s stress response inventory, * P < .05, ** P < .01, *** P < .001.

The differences of mood states and health-related quality of life between experimental and control groups were measured by using repeated measures ANOVA. The result were significant in anger–hostility (f= 4.189, P = .047, $η$ _p²= .097), vigor–activity (f= 12.600, P = .001, $η$ _p²= .244), fatigue–inertia (f= 4.307, P = .045, $η$ _p²= .099), and EQ-VAS (f= 17.670, P = .001, $η$ _p²= .306).

A significant difference in pre-test tension–anxiety scores on the POMS between the groups (t= 2.884, df= 39, P = .006) were also observed. Therefore, we conducted another ANCOVA while controlling for the pre-test tension–anxiety scores. The differences between the groups in tension–anxiety scores, after controlling for pre-test score. The differences in changes were not significant (f= 3.982, P = .053).

After participating in the forest therapy, the scores of tension–anxiety (t= −2.180, df= 20, P = .041), depression–dejection (t= −4.771, df= 20, P = .001), anger–hostility (t= −2.245, df = 20, P = .004), fatigue–inertia (t= −5.579, df= 20, P = .001), and total POMS (t= −3.704, df= 20, P = .001) showed significant decreases as shown in Table 5. In contrast, although a decreasing tendency was also observed in the control group for all variables except for confusion–bewilderment, only anger–hostility (t= −2.179, df= 19, P = .042) showed a significant change. In the experimental group, vigor–activity (t= 3.487, df= 20, P = .002) and EQ-VAS (t= 4.397, df= 20, P = .001) showed significant increases over the study period. However, in the control group, vigor–activity and EQ-VAS showed no significant change.

Table 5.

Comparison of POMS and EQ-VAS scores between pre- and post-test within experimental and control groups.

Variables	Sub-Factors	Group	M(SD)		t	p	d
Variables	Sub-Factors	Group	Post	Pre	t	p	d
POMS	Tension–Anxiety	Experimental	−2.00 (2.07)	−.81 (2.54)	−2.180^*	.041	.48
	Tension–Anxiety	Control	6.75 (10.93)	7.60 (13.12)	−.400	.694	.09
	Depression–Dejection	Experimental	1.62 (4.25)	7.81 (8.61)	−4.771^***	.001	1.04
	Depression–Dejection	Control	8.10 (10.86)	9.75 (12.99)	−.864	.398	.19
	Anger–Hostility	Experimental	1.52 (5.24)	8.90 (11.37)	−3.245^**	.004	.71
	Anger–Hostility	Control	7.40 (6.16)	9.60 (8.47)	−2.179^*	.042	.49
	Vigour–Activity	Experimental	18.00 (6.74)	12.76 (6.03)	3.487^**	.002	.76
	Vigour–Activity	Control	13.65 (7.12)	14.65 (5.69)	−1.153	.263	.26
	Fatigue–Inertia	Experimental	2.33 (3.26)	7.29 (4.72)	−5.579^***	.001	1.22
	Fatigue–Inertia	Control	6.30 (5.26)	7.85 (7.01)	−1.109	.281	.25
	Confusion-bewilderment	Experimental	−1.81 (2.44)	−1.00 (2.85)	−1.246	.227	.27
	Confusion-bewilderment	Control	.30 (3.37)	.25 (2.31)	.054	.958	.01
	Total	Experimental	19.86 (12.65)	34.81 (21.5)	−3.704^**	.001	.81
	Total	Control	42.35 (28.26)	49.50 (38.07)	−.986	.337	.22
EQ-VAS		Experimental	83.19 (10.01)	70.95 (14.11)	4.397^***	.001	.96
EQ-VAS		Control	76.48 (12.32)	76.81 (11.08)	−.305	.764	.07

Note: POMS: Profile of Mood States, EQ-VAS: EuroQol Visual Analog Scale, * P < .05, ** P < .01, *** P < .001.

Discussion

A difference in the incline of NK cell activity between both groups was observed. NK cell activity was increased significantly for those who took part in the forest therapy program, while this increase was not significantly different from that in the control group. This result suggested that the forest therapy program has the possibility of increasing the level of immunity. This result was in line with the results of a study.³⁴

The decline in salivary cortisol within the experimental group was significant. The result suggested that the participants in the forest therapy became physiologically less stressful. This result was in concordance with results from WSRI. Hence, the forest therapy seemed to aid participants to be relieved from stress. Notably, attention restoration effects³⁶ have been suggested as contributing factor, the mental health and wellbeing outcomes of MBSR are greater when it carried out in a natural outdoor environment compared with indoor or built environments.³⁷

The forest therapy contributed significantly to decreases in depression, anger, and somatization symptoms. Notably, we had obtained comparable results from the previous study.²⁴ in which the forest therapy program, schedule, participating experts, diet, duration, and study design were similar to those of this study. The previous study²⁴ indicated that the effect size of somatization (d = .519) and anger (d = .749) symptoms and total stress score (d = .540) were medium in forest therapy group. In comparison, this study identified that the effect size of somatization (d = .992) and anger (d = .941) symptoms and total stress score (d = 1.314) were large. This difference may illustrate the forest therapy program in this study has contributed to a higher effect in decreasing stress symptoms among participants. One of the possible reasons can be the motivation of the participants. As pointed out in the previous report,²⁴ some participants had not participated in the program on a completely voluntary basis and thus a bit less motivated, while the participants in this study were on a completely voluntary basis and very motivated to be willing to join. This result highlights the importance of participants’ attitude in achieving better therapeutic outcomes. The forest therapy should not be conceived as an extension of the work schedule as indicated from a previous study.²⁴

Additionally, the level of lack of motivation, lack of concentration, and leave of absence from work decreased significantly more in the experimental group than in the control group. This suggests that the 3 day forest therapy program could increase the level of motivation, concentration, and reduce leave of absence resulting from work-related stress.

In terms of changes in mood states, in the experimental group, found significantly higher decreases in anger-hostility, and fatigue–inertia and a significantly higher increase in vigour–activity compared to the control group. These results suggest that the forest therapy program helped to increase vitality and vigour and otherwise positively transform participants' mood states. Considering unpredictable travel time due to heavy traffic on the afternoon, exogenous variables such as fatigue and other psychological imprecation may have influenced the result of post-testing. Thus, this multidisciplinary therapeutic intervention on stress could be suggested to have positive effects, especially for the magnitude of the effect size for the total mood states score was large (d = .081).

As for the health-related quality of life, this study has shown similar results that a previous study in which illustrated visiting forest environment has increased health-related quality of life for patients with stress-related illness.³³ Moreover, this study has reported similar results that a previous study in which indicated implementing forest therapy and mindfulness-based intervention in nature have increased health-related quality of life³⁴ and stress level.³⁵ for patients with chronic widespread pain. In terms of changes in HRV, the result identified a significant increase in heart rate. An elevated heart rate in control group is unknown. Both significant inclines in SDNN, RMSSD, TP, and HF norm and declines in LF/HF ratio and LF norm illustrated that the forest therapy program contributed to participants’ state of relaxation. Finally, added to the current knowledge on the positive effects of the forest therapy on middle aged male,²⁵this study added the positive effects on adult via the result of the forest therapy.

The limitations of this study were as follows. First, it should be clarified whether similar results can be obtained and whether the results remain significant after increasing the number of participants to add validity for the indices that showed significant changes after the forest therapy intervention. Second, the study participants known to exhibit work-related stress because of their high degree of responsibility at work and considerable domestic stress. However, since the level of domestic stress of the participants of the study was not measured, we could not measure changes in domestic stress after the forest therapy treatment. Third, a 3 day retreat was conducted in this study, and, in general, this program exerted positive influences on the psychological and physical health of the participants. However, the durability of the effects of this program after the participants had returned to their work could not be confirmed. Fourth, as a limitation remarked in a study³⁴ the individual effects of each therapeutic components included in the forest therapy were not tested. Instead of comparing a specific treatment this study has tested the reproduction-effects of the forest therapy among manufacturing industry workers. Fifths, although positive outcomes by the result of the treatment, future research should test the duration of forest therapy may extent over 3 days and comparison with other types of environments (eg, coastal/rural). Lastly, longitudinal research could also be beneficial, especially when evaluating the effects of forest therapy on specific stressors.

Conclusions

The forest therapy led to significant decreases in work-related stress and improved positive mood states. This suggests that a forest therapy could be an effective stress management strategy for workers in the manufacturing industry.

Footnotes

Acknowledgments

This study was carried out with the support of “Forest Science and Technology Projects (Project No. S111115L020100)” provided by Korea Forest Service.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Joo Moon

References

OECD , Hours worked (indicator). 2022. doi: 10.1787/47be1c78-en (Accessed on 26 July 2021).

Chang

Koh

Kang

, et al. Epidemiology of psychosocial distress in Korean employees. Journal of preventive medicine and public health= Yebang Uihakhoe chi. 2005;38(1):25-37.

National Institute for Occupational Safety and Health (NIOSH)

Stressat Work. Centers for Disease Control and Prevention, 99-101. U. S. Department of Health and Human Services; 1999:26.

Krueger

. Sustained work, fatigue, sleep loss and performance: A review of the issues. Work Stress. 1989;3(2):129-141.

Hanebuth

Meinel

Fischer

. Health-related quality of life, psychosocial work conditions, and absenteeism in an industrial sample of blue-and white-collar employees: a comparison of potential predictors. J Occup Environ Med. 2006;48(1):28-37.

Welch

. Creature comforts. People Manag. 1996;2:20-24.

Berry

. Psychology at Work: An Introduction to Industrial and Organizational Psychology. New York: McGrand Hill. Inc.; 1998.

Pickering

. Mental stress as a causal factor in the development of hypertension and cardiovascular disease. Curr Hypertens Rep. 2001;3(3):249-254.

Kiecolt-Glaser

Glaser

. Depression and immune function: Central pathways to morbidity and mortality. J Psychosom Res. 2002;53(4):873-876.

10.

Ambrose-Oji

. Mindfulness practice in woods and forests: An evidence review. Research Report for the Mersey Forest, Forest Research. In: Alice Holt Lodge Farnham. 2013.

11.

Abbott

Whear

Rodgers

, et al. Effectiveness of mindfulness-based stress reduction and mindfulness based cognitive therapy in vascular disease: A systematic review and meta-analysis of randomised controlled trials. J Psychosom Res. 2014;76(5):341-351.

12.

Smith

. Mindfulness‐based stress reduction: An intervention to enhance the effectiveness of nurses’ coping with work‐related stress. International journal of nursing knowledge. 2014;25(2):119-130.

13.

Alvarsson

Wiens

Nilsson

. Stress recovery during exposure to nature sound and environmental noise. Int J Environ Res Publ Health. 2010;7(3):1036-1046.

14.

Netterstrøm

Bech

. Effect of a multidisciplinary stress treatment programme on the return to work rate for persons with work-related stress. A non-randomized controlled study from a stress clinic. BMC Publ Health. 2010;10(1):658.

15.

Kaplan

. Nature at the doorstep: Residential satisfaction and the nearby environment. Journal of Architectural and Planning Research 1985;(115-127):115-127.

16.

Kawada

. Effect of forest therapy on the human psycho-neuro-endocrino-immune network. Nihon eiseigaku zasshi. Japanese journal of hygiene. 2011;66(4):645-650.

17.

Miyazaki

Nakamizo

Tsuji

, et al. Enhancement of NK cell activity and Th1 immunity in healthy subjects by orally administered fucoidan mix. J Immunol. 2012;162:35.

18.

Joung

Kim

Choi

, et al. The prefrontal cortex activity and psychological effects of viewing forest landscapes in autumn season. Int J Environ Res Publ Health. 2015;12(7):7235-7243.

19.

Jung

Woo

Ryu

. Effect of frequency of using forest environment on workers stress: A comparative study on workers in medical and counseling service institution. J Kor For Soc. 2014;103(1):129-136.

20.

Sonntag-Öström

Nordin

Lundell

, et al. Restorative effects of visits to urban and forest environments in patients with exhaustion disorder. Urban For Urban Green. 2014;13(2):344-354.

21.

Laviana

. Assessing the Impact of Plants in the Simulated Office Environment: A Human Factors Approach. PhD Dissertation. Manhattan, KS: Kansas State University; 1985.

22.

Largo-Wight

Chen

Dodd

Weiler

. Healthy workplaces: The effects of nature contact at work on employee stress and health. Publ Health Rep. 2011;126(1_suppl l):124-130.

23.

Yamaguchi

Deguchi

Miyazaki

. The effects of exercise in forest and urban environments on sympathetic nervous activity of normal young adults. J Int Med Res. 2006;34(2):152-159.

24.

Jung

Woo

Ryu

. Effect of a forest therapy program and the forest environment on female workers’ stress. Urban For Urban Green. 2015;14(2):274-281.

25.

Ochiai

Ikei

Song

, et al. Physiological and psychological effects of forest therapy on middle-aged males with high-normal blood pressure. Int J Environ Res Publ Health. 2015;12(3):2532-2542.

26.

Faul

Erdfelder

Buchner

Lang

. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behav Res Methods . 2009;41(4):1149-1160.

27.

Dave

Xiang

Rehm

Marshall

. Stress and allergic diseases. Immunology and Allergy Clinics. 2011;31(1):55-68.

28.

Choi

Kang

Woo

. Development and validation of a modified form of the stress response inventory for workers. Journal of Korean Neuropsychiatric Association. 2006;45(6):541-553.

29.

Koh

Park

Kim

. Development of the stress response inventory. Journal of Korean Neuropsychiatric Association. 2000;39(4):707-719.

30.

Hellhammer

Wüst

Kudielka

. Salivary cortisol as a biomarker in stress research. Psychoneuroendocrinology. 2009;34(2):163-171.

31.

Obradovic

Lal

Liedgens

. Validity and responsiveness of EuroQol-5 dimension (EQ-5D) versus Short Form-6 dimension (SF-6D) questionnaire in chronic pain. Health Qual Life Outcome. 2013;11(1):110.

32.

McNair

Lorr

Droppleman

. Profiles of Mood States. San Diego: Educational and Industrial Testing Services; 1971.

33.

Corazon

Stigsdotter

Jensen

AGC

, et al. Development of the nature-based therapy concept for patients with stress-related illness at the Danish healing forest garden Nacadia. Journal of Therapeutic Horticulture. 2010;20:33-51.

34.

Han

Choi

Jeon

Yoon

Woo

Kim

. The effects of forest therapy on coping with chronic widespread pain: Physiological and psychological differences between participants in a forest therapy program and a control group. Int J Environ Res Publ Health. 2016;13(3):255.

35.

Choi

Hahm

Jeon

Han

Kim

Woo

. Effects of Mindfulness-Based Mandala Coloring, Made in Nature, on Chronic Widespread Musculoskeletal Pain: Randomized Trial. Healthcare. Multidisciplinary Digital Publishing Institute. 2021;9(6):642.

36.

Hartig

Mang

Evans

. Restorative effects of natural environment experiences. Environ Behav. 1991;23(1):3-26.

37.

Choe

Jorgensen

Sheffield

. Does a natural environment enhance the effectiveness of Mindfulness-Based Stress Reduction (MBSR)? Examining the mental health and wellbeing, and nature connectedness benefits. Landsc Urban Plann. 2020;202:103886.

38.

Bianchi

Mainardi

Cerutti

. Non-conventional measurements from ECG recordings: Towards an improvement of diagnostic properties. International Journal of Bioelectromagnetism. 2003;5(1):171-174.

The Effects of a Forest Therapy on Work-Related Stress for Employees in the Manufacturing Industry: Randomized Control Study

Abstract

Background

Objective

Methods

Results

Conclusions

Keywords

Introduction

Materials and Methods

Sample Size Calculation

Participants and Design

Experimental Treatment

Primary Assessments

Secondary Assements

Procedure

Statistical Analyses

Results

Physiological Assesement

Psychological Assesement

Discussion

Conclusions

Footnotes

Acknowledgments

Declaration of Conflicting Interests

Funding

ORCID iD

References