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sustainability
Article
Evaluating the Mental-Health Positive Impacts of Agritourism;
A Case Study from South Korea
Mehdi Rezaei 1, Doohwan Kim 1, Ahad Alizadeh 2and Ladan Rokni 3, *
Citation: Rezaei, M.; Kim, D.;
Alizadeh, A.; Rokni, L. Evaluating the
Mental-Health Positive Impacts of
Agritourism; A Case Study from
South Korea. Sustainability 2021,13,
8712. https://doi.org/10.3390/
su13168712
Academic Editors:
Elisabeth Kastenholz, Bernard Lane
and Maria João Carneiro
Received: 22 May 2021
Accepted: 29 July 2021
Published: 4 August 2021
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4.0/).
1Deptarment of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Korea;
mehdi.r5858@gmail.com (M.R.); kimdh@konkuk.ac.kr (D.K.)
2Metabolic Diseases Research Center, Research Institute for Prevention of Non-Communicable Diseases,
Qazvin University of Medical Sciences, Qazvin 15315-34199, Iran; st.alizadeh@gmail.com
3Asia Contents Institute, Konkuk University, Seoul 05029, Korea
*Correspondence: rokni.ladan@gmail.com
Abstract:
The stressful lifestyle of urban dwellers has increased the demand for green-based leisure
activities; considering such growing demand, this paper investigated the potential mental health
benefits of agritourism activities. The assessments were based on a questionnaire survey of two
groups: visitors of agritourism sites around Seoul and a control group staying home (n= 200). In
addition to measuring the participants’ well-being level and stress level, they were also asked to
self-estimate their immediate mood after their activities of the day. The analysis was conducted
with R version 4.1.0 to explore the potential relationships and interactions between the activity
of the day, perceived psychological factors, and the immediate emotional outcomes. Findings
reveal that visitors to the agritourism sites perceived considerable improvement in their immediate
mood compared to the control group who stayed home. Results indicate a significant interaction
between self-reported wellbeing and agritourism activities and a combined effect on improved mood.
Therefore, agritourism can potentially be a resource for a positive mood boost and improved mental
health. The suggested practical implications can be applied as strategies to evoke the feeling of more
connection to the agritourism activities and raise awareness of potential mental health outcomes.
Keywords: agritourism; mental health; farm tourism; psychological effects; mood boost
1. Introduction
Fast-growing urbanisation has led to mental and physical health problems for city
dwellers; its associated outcomes have turned green-based leisure activities into a necessity.
Green-space exposure can play a crucial role in promoting the health and wellbeing of
people [
1
]. It provides an opportunity for people to escape from their regular lives and
stressful environments through engaging in outdoor activities [
2
]. It is believed that indi-
viduals living in areas with no green space may be more vulnerable to the negative impacts
of stressful life events. The reason is that people have fewer opportunities for nature-based
coping strategies than individuals living in areas with abundant green space [3,4].
There is evidence for a positive relationship between access to green or natural environ-
ments and people’s perceived general health [5], mental health [6,7], physical health [8,9],
social health [
7
,
10
,
11
], and it can even lead to an improved mood [
12
] or reduced stress
and anxiety [6,7,13].
Most research on the outcomes of green-space exposure has investigated whether
access and specific facilities are associated with wellbeing. In contrast, few studies have
focused on the type of green space and how it can impact psychological mood and mental
health. This paper addresses one particular form of green-based leisure activity, namely,
‘agritourism’. It is a unique form of tourism activity, linked to ecotourism and rural tourism,
involving both natural and cultural activities with a focus on sustainability.
Sustainability 2021,13, 8712. https://doi.org/10.3390/su13168712 https://www.mdpi.com/journal/sustainability
Sustainability 2021,13, 8712 2 of 16
There is little universal understanding of an agritourism definition. Disagreement
exists regarding its characteristics and its boundaries [
14
]. It is accepted that this farm-
based tourist experience has, however, played an innovative role in diversifying many
farming businesses [
15
]. It involves farming-related activities and agricultural settings for
entertainment or education on a working farm [
16
]. It is both a form of ‘supplementary
business’ for farmers [
17
] and a new form of tourism [
18
]. Definitions of agritourism have
been classified into three different perspectives: defining it as a component, or from the
perspective of agricultural activity, or the development of rural communities [
19
]. Much
depends on different combinations of key characteristics, the nature of the interaction
between visitors and agriculture, and the level of experiencing authentic agriculture [
20
].
Two factors of ‘the authenticity of the activity’ and the ‘possible participation in agricultural
life’ can differentiate authentic agritourism from other forms of rural tourism [
21
]. Chase
et al. (2018) tried to classify and represent all the activities in agritourism in two main
categories: core and peripheral activities. The classification was based on five criteria:
direct sales, education, hospitality, outdoor recreation, and entertainment [21].
This study considers agritourism a unique ‘experience’ or ‘activity’ that can allow
urban dwellers to participate and reconnect to nature through agriculture on a working
farm [
14
,
22
]. Moreover, visiting rural green spaces gives a chance to forget the hectic urban
life; it allows the tourist to focus on their own and society’s general wellbeing. Agritourism
activities can provide the feel of connection with nature and offer visitors the nostalgia of a
“quiet” traditional life [23].
1.1. Green Environments and Mental Health
Searching in green-based tourism journals, we found that much research has been
conducted from different perspectives on this and related issues. Some studies explored
broad perspectives of the impacts of rural tourism on quality of life [
24
,
25
] or on life
satisfaction due to the holiday experience [
26
]. In contrast, some studies focused on specific
tourism behaviour [
25
] or from the perspective of medical issue examinations [
27
,
28
]. The
main focus, however, has been on outdoor activities emphasising personal growth and
self-discovery [29].
It is essential to note the specific positive factors contributing to physical activity,
social interaction, or a combination of different activities [
30
]. The health benefits can
combine physiological and psychological health. Access, quantity, and types of green areas
were mentioned as contributing factors to mental health benefits [
31
]. Three behavioural
mechanisms have been involved [
13
]. The type of contact to the environment [
11
], the
opportunity for social contact to improve mood and stress level [
32
], and the environmental
design in creating conditions ‘attractive enough to recover from demanding situations of
urban lifestyle’ [33].
Miller et al. (2008) investigated the contribution of parks and protected areas to human
health and wellbeing. They classified the associated wellbeing as physical, mental, spiritual,
social, and environmental, and in each context, they mentioned the relevant benefits at
various levels [
34
,
35
]. Some studies mentioned the increased approval of nature protection
by green spaces’ visitors [
36
,
37
]. Several studies revealed increased group cohesion [
38
,
39
]
and more pro-social behaviour [
40
]. From the perspectives of the mental and spiritual
benefits, the health effects of green resources tourism include the feeling of a more positive
self-concept and increased self-esteem [41–43].
Two beneficial mental health effects were repeatedly mentioned: enhancement in
wellbeing [
30
] and reduction in stress [
13
,
44
,
45
]. Two studies targeted children in their
research. They found that the amount of nature in people’s environments had a strong
relationship with depression and anxiety disorder and confirmed its impact on decreasing
stress [
46
,
47
]. Thompson et al. confirmed the link between more green space and less
stress in deprived communities [
13
] and social tourists who received financial support [
48
].
Similar results were found for young adults [
35
]. The quantity of visiting green spaces
effective in the reported stress-related illnesses (the number of times people visit and the
Sustainability 2021,13, 8712 3 of 16
duration of their park visits) [
44
] and the quality and success of a green-based program can
increase self-efficacy, mindfulness, and subjective wellbeing. It may reduce feelings of time
pressure and mental stress [
35
]. The positive contribution of green-based leisure time is
important for both long vacations [24] and for short visits longer than 20 minutes [30].
Wendelboe-Nelson et al. (2019) investigated the context of green-space exposure
and its association with mental health wellbeing through a scoping review approach.
They note that different green spaces (e.g., recreational, residential, urban, or rural) may
affect mental health well-being differently [
49
]. Therefore, studying agritourism as a new
beneficial environment for mental health, with different functions and activities, might
affect new contexts.
1.2. Mental Health: Well-Being, Stress
Based on the World Health Organisation (WHO) definition, mental health is not
only the absence of mental disorders but also has a broader state of subjective wellbeing,
comprising physical, mental, and social wellbeing factors. The WHO has emphasised
the effective functioning of time spent in the countryside for both the individual and the
community, allowing individuals to realise their abilities, cope with the everyday stresses
of life, work productively and fruitfully, and contribute to their community [
50
]. Although
the definition presented by WHO is still the main reference to describe mental health,
there is no universal definition of mental health wellbeing, which makes it difficult for
researchers in this subject. A review study on the wellbeing outcomes of green-space
exposure suggested a definition of mental health wellbeing as a starting point in which
wellbeing incorporates more social aspects and the potential of individuals rather than
physical health [
49
]. There is also a translation problem; it is sometimes difficult to find an
appropriate comparable synonym when wellbeing is translated into other languages [51].
In social and behavioural science, researchers need to prove reliability and valid-
ity when measuring mental health; therefore, it is recommended to apply the standard
models [49].
Wellbeing can often be described in terms of happiness, which is a fundamental goal
of society [
52
]. The literature on subjective wellbeing broadly differentiates long-term life
satisfaction from short-term emotional wellbeing [
35
,
53
]. Stress, the other core variable
in this study, is regarded as one of the most critical factors in evaluating mental health in
modern society [
44
]. Stress is considered a type of adjustment activated by physical or
psychological tensions [
4
]. Contact with nature and relieving stress has been practically
shown to have a significant relationship [
49
]. However, there is no homogeneous result
regarding green spaces and the mental health relationship [47].
Living conditions and environments support mental health, since these two factors
allow people to adopt and maintain healthy lifestyles [
40
]. However, it is not easy to
consider all the contextual factors that might affect mental health wellbeing outcomes due
to the lack of information [49].
1.3. Agritourism in Korea
South Korea is a high per capita GDP country with a dynamic and flourishing econ-
omy; however, an unbalanced growth strategy was adopted to modernise the economy
quickly. It seems that the achievements have been at a high cost to environmental health
and the imbalance between urban and rural development [
54
]. Due to such rapid transfor-
mation, rural and urban areas suffered from socio-economic problems [
55
]. It led to high
levels of stress and life dissatisfaction in the metropolitan area, especially among the young
generation [56].
In the fourth national territorial plan (2000 to 2020), the government’s main focus was
to launch strategies that could eliminate gaps between urban and rural areas by diversifying
rural economic activities, establishing a regional innovation system, and encouraging rural–
urban interactions. Hence, the plan has been to develop rural areas through innovative
activities, specifically, encouraging farm diversification through tourism activities. Farms
Sustainability 2021,13, 8712 4 of 16
Tour appeared as a new concept, with activity farming-experience centres, restaurants,
resorts, and accommodations for visitors. Later the new policy changed and focused
on cooperation and community-based business. Nowadays, agritourism in South Korea
includes cooperatively developed farm tourism by at least five households [57].
The government supports agritourism as a rural tourism project, especially “rural
theme villages”, the promotion of organic farming, and encouraging engagement in har-
vesting events [52,58].
1.4. Stress in South Korean Society
In South Korea, suicide is one of the most common causes of death, seemingly linked
to living in a high-stress society. It was estimated that 90% of people who committed
suicide in 2016 had a diagnosable psychiatric illness, such as depression or anxiety, mainly
caused by stress [
59
]. Surveys show that 56.5% of adolescents suffer from stress, and more
than 2 million Koreans suffer from a major depressive disorder [56].
Given the contemporary situation in South Korea and the proven relationship between
green-resources tourism with some aspects of mental health, it was hypothesised that:
•Agritourism activities might contribute to improve the immediate mood and further
improve mental health.
To our knowledge, there has been no study to find evidence of the agritourism benefits
of mental health. This research aimed to test which, if any, mental health benefits are
related to agritourism experiences. Two dimensions of mental health were at the core of
this research: perceived wellbeing and perceived stress. It was hypothesised that:
•There might be an interaction between self-reported wellbeing and agritourism.
•There might be an interaction between self-reported stress and agritourism.
2. Materials and Methods
2.1. Study Area
This study was conducted in 5 selected agritourism sites in the Seoul metropolitan
area located in northwest South Korea. A population of about 25 million ranks it among
the largest metropolitan areas in the world (website of the Seoul Metropolitan Government,
2020). This city was chosen because of its population density, and its hectic lifestyles.
Citizens in Seoul often complain of their lack of adequate ‘time’ and ‘space’ for outdoor
leisure activities.
Two types of agritourism sites are typical in South Korea. The first group mainly focus
on non-agricultural activities for short-visit tourists, such as farm animals, and several
associated entertainments are provided mainly for families with children. The second
group comprises agricultural activities wherein the tourism facilities and activities are
provided as supplements.
The first types were excluded, and among the second type of the available agritourism
sites, the most visited sites (relatively) were found. To homogenize the selected study sites
and to prevent site selection bias, we tried to consider several effective factors (49) as the
inclusion criteria:
•Having easy access for visitors from Seoul city
•Being located out of the city area
•Providing both farming and leisure activities for visitors
•Providing both harvesting events and animal farms even on a small scale
•Also, we tried to select sites in different directions around the city of Seoul
The main agricultural activities on the selected sites were cultivating vegetables “(corn,
tomato, cucumber, cabbage, tomato, etc.)”; animal farms concentrated on chicken and pigs.
In addition, these sites comprised 1–4 small buildings, one or more pavilions for small
social gatherings, and a large outdoor area. The other common point among all the sites
was the managed and well-organized environment, which is likely to cause more interest
in Korean culture. In addition, all the sites were working and managed on a small scale.
Sustainability 2021,13, 8712 5 of 16
The main tourism activities offered in the selected sites were harvesting activities, such
as pick your own services, farm-to-table meals (mainly barbeque and local vegetables), and
animal feeding. Based on the authors’ observation during the data collection, each site had
10–30 domestic visitors during the weekend (during the harvesting time).
2.2. Measures
Even though several behavioural and health variables have been involved in previous
research on the relationship between nature and mental health, we decided to focus on
wellbeing and stress since we found them relevant to Korean society. Both have been
repeatedly tested in previous studies. The participants’ feelings after agritourism were also
asked the four questions about their ‘present emotional state’ mentioned below.
2.2.1. Perceived Stress
Perceived Stress (ST): Perceived stress was assessed with the Perceived Stress Question-
naire (PSQ) [
60
]. This instrument can subjectively measure experienced stress in multiple
dimensions and is widely recognised in research on stress and well-being [
61
,
62
]. The PSQ
items can be arranged into four subscales, including worry, tension, joy, and demand. In
the context of the present study, the PSQ dimensions seem to be of relevance. For instance,
the subscale “demand” refers to the external demands, such as time pressure and work
overload [
61
], which is believed to be common in Korean society [
63
] (e.g., “You have
too many things to do”; “You feel you’re in a hurry”). Perceived stress was self-reported
(during the last year or two) on four scales of ‘almost’, ‘sometimes’, ‘often’, and ‘usually’.
2.2.2. Wellbeing
Well-being (WB): Searching the instruments developed to measure wellbeing, we
found the WHO (Five) Wellbeing Index (1998 version) as the best to capture the intended
attitude of the participants [
64
]. It measured perceived mental wellbeing during the last
two weeks on a 6-point Likert scale (from ‘all of the time’, 5, to ‘at no time’, 0).
2.2.3. Present Emotional State
Present emotional state (PES): The post-experience questions captured the perceived
state of the ‘immediate mood’. It was measured with four general questions that referred
to the respondent’s present emotional state, ‘How happy are you at this moment, ‘How
do you think today’s experiences made you less stressed’. The other questions assessed
the extent to which participants perceived agritourism activities/environment as mood
boosting and if it had affected their present feeling and stress levels. It used a 5-point rating
scale with higher values indicating greater happiness.
2.3. Sample and Study Design
The participants were 200 members of the community of the ‘Global Agricultural
Development Cooperation Center’ in Seoul. The main role of this community is educa-
tion in terms of agriculture, with different projects designed to motivate the members to
engage in agri-oriented activities, mainly in rural areas. Several educational courses and
practical projects are offered throughout the year. The main reason for selecting members
of this community was that almost all are familiar with “green” activities. They were also
interested in participating in agricultural activities and group-visiting farm areas.
After receiving permission from managers, lecturers were informed of the aim and
procedure of research and were requested to announce this research and encourage the
members to participate.
Members who agreed to participate sent an agreement letter to the corresponding
author via email. The participants were informed briefly about the procedure. They agreed
to travel to an agritourism site or stay at home for one day during weekends between July
and October 2019. They had no choice to select one of the programs themselves; however,
they were free to select the date based on their schedule. Therefore, the initial inclusion
Sustainability 2021,13, 8712 6 of 16
criteria were: acceptance to spend one weekend day at home and having no particular
plan or activity, except their daily routine with housework, and expressing their interest in
participating in agritourism activities during the lecture.
After meeting those criteria, the lecturer provided a list of potential participants with
their emails. A code was given to each email address, and performing ‘randomisation’,
200 coded-participants were allocated to two groups. Then, it proceeded through ‘random
blocking’ in R software (version 4.1.0), using the ‘agricolate’ package.
First group: ‘Visiting agritourism sites (Agrit-group)’
The members of this group were informed about their given plan via email. They
were requested to select one day of a weekend (between the given months) to visit one of
the selected agritourism sites around the Seoul metropolitan area and spend the whole day
there. They were requested to stay on the site for more than 4 to 5 h to ensure that they had
enough time to engage in the activities.
The participants in this group informed the authors about their schedule and their
selected site to visit. One author also travelled to the same site on the same day to distribute
and collect the questionnaires. Sampling took place on almost fully fair-weather weekends.
Visitors were welcomed at the entrance door by the author. The same sampling effort
was allocated to different sites. Participants were asked to complete the first part of the
questionnaire before starting their activities on the site. This part of the questionnaire
captured information on participants’ socio-demographic information, as well as their
perceived wellbeing and stress level, through two sets of 5 items and 30 items that included
two standardised measures: the wellbeing index [
64
] and stress (PSQ) [
60
]. The author
waited at the sites until the participants completed the site visit and their engagement
in activities. They asked them to complete the second part of the questionnaire before
their site visit in the morning. The respondents were asked to self-estimate their ‘present
emotional state’. The visitors did not have access to their pre-site visit responses when
completing the post-site visit questionnaire.
Second group: ‘Spending the weekend at home (Routine group)’
The members of this group were informed about the requested plan via Email, and
they were asked to spend one day of a weekend at home (between the given months). All
the selected participants were contacted via email in the early morning of the selected day
for data collection and were given two hours to fill out the first part of the questionnaire,
which was similar to the one given to the Agrit-group. To ensure consistency of under-
standing between participants, an explanation was provided in the email, and the direct
contact number of one of the authors was provided in the case of having any inquiry.
Before the evening, a second email was sent to the participants. Just the same as the
questionnaire for Agrit-group, the respondents were asked to self-estimate their ‘present
emotional state’.
Eliminating Bias
Various procedural remedies were utilised to control the risk of common method
variance [
65
]. In the email sent to all the participants of both groups, it was mentioned
that their information would be kept confidential, and they were informed that there were
no right or wrong answers in the questionnaire. To ensure consistency of understanding
between participants (in both groups), we explained what was meant by ‘mental health’.
Similar to Wolf and Wohlfart (2014), we clarified definitions of health vs. wellbeing for the
participants following McGregorTan Research (2007) [
1
]. We defined wellbeing as mental
health, and overall feeling as relating to mind, body, spirit, emotional state, and peace
levels. Moreover, a self-administered manner was applied to filling in the questionnaires,
which guaranteed anonymity.
Likewise, the data were gathered in two time periods, in the morning and evening.
Such data collection practices are consistent with the suggested remedies for minimising
common method bias on the association among the variables [65].
Sustainability 2021,13, 8712 7 of 16
Even though it is believed that environmental and personal exposure to green space
might impact the results, it is also suggested that including standardised quantitative data
collection methods will allow a better understanding of the underlying factors (review).
Therefore, in this study, we adopted randomisation to divide the participants into two
groups of Agrit and control to have ideal homogenised participants in both groups and to
adjust the impact of some confounding factors [
35
,
49
]. Additionally, it was reported that
the study location, type of assessment, and type of exposure moderated nature’s positive
effects [
50
]; therefore in the current research, we tried to homogenise all those confounding
factors for all the participants.
2.4. Analyses
Data from the questionnaire responses were analysed with R version 4.1.0. The first
set of analyses involved a basic descriptive analysis of the demographic variables and the
psychological measurements. The variables were compared, and p-values were reported
to show the homogeneity of the factors for the two groups, Agrit and Routine. Pearson’s
correlation coefficients were also performed on all the involved variables.
In the second part of the analysis, several tests were conducted to address the research
questions. The potential general effects of the activity of the day, demographic variables,
WB, and ST on PES were tested through multivariate analysis of variance (MANOVA).
Moreover, univariate analysis of variance (ANOVA) was performed to test the same effects
on each item of PES separately. The reported Pillai’s trace represented the percentage of
the PES’s variation determined by the independent variables.
Further, to measure the strength of the impacts, multiple linear regressions were
conducted. The effects of the Agrit-group and Routine-group on PES were compared,
and the represented amount of beta (regression coefficient) showed the strength of such
difference. Similarly, the same method was performed on WB and ST to test the strength of
their effects on PES. The score of WB and ST was calculated for each participant through
the formula designed by the mentioned references [
31
,
51
]. Additionally, four items of PES
were combined, and the strength of the effects was computed on all the items at once.
The third and final part of the analysis dealt with testing the interactions; Data were
split into Agrit-group and Routine-group at this stage. Multiple linear regression tests were
performed on those variables that had significant correlations in the Pearson correlations
test. Accordingly, PES was considered a dependent variable, and the interactions effects of
wellbeing and stress with the activity of the day were estimated.
3. Results
3.1. Measurement Results
Before any intervention, the demographic variables were adjusted to ensure their bal-
ance in both groups; it was required for performing randomisation. Moreover, by analysing
the demographic variables, we found that samples were almost evenly represented by both
genders, with an average age of 31–40. This age group had the highest percentage of the
participant (28.5%), and it was followed by participants of the age group between 21–30
and then 41–50 (Table 1).
Later, Pearson correlation coefficients were performed between all the variables. The
result indicated that, while WB and PES were significantly correlated for the Agrit-group,
such correlations were insignificant for the Routine-group. However, ST did not present
correlations with any of the variables.
Sustainability 2021,13, 8712 8 of 16
Table 1.
Demographic and psychological characteristics of participants in two groups of Agrit
and Routine.
Factors Total Routine (n= 100) Agrit (n= 100) pValue
Age
<20 36 (18%) 17 (17%) 19 (19%)
0.022
21–30 42 (21%) 18 (18%) 24 (24%)
31–40 57 (28.5%) 31 (31%) 26 (26%)
41–50 37 (18.5%) 15 (15%) 22 (22%)
51–60 22 (11%) 14 (14%) 8 (8%)
61–70 4 (2%) 3 (3%) 1 (1%)
>71 2 (1%) 2 (2%) 0 (0%)
Gender Female 98 (49%) 51 (51%) 47 (47%) 0.673
Male 102 (51%) 49 (49%) 53 (53%)
WB 18.50 ±3.53 17.54 ±3.37 19.45 ±3.44 <0.001
ST 76.23 ±9.18 76.40 ±7.41 76.06 ±10.75 0.681
PES 1 3.54 ±1.04 2.98 ±1.03 4.10 ±0.67 <0.001
PES 2 3.50 ±1.12 2.86 ±1.05 4.13 ±0.76 <0.001
PES 3 3.33 ±1.23 2.52 ±1.06 4.14 ±0.78 <0.001
PES 4 3.62 ±0.93 3.13 ±0.86 4.11 ±0.72 <0.001
Total PES 13.98 ±3.47 11.49 ±2.48 16.48 ±2.35 <0.001
3.2. Test of the Research Questions
To test if the activity of the day can contribute to an improved mood (PES), both
MANOVA and ANOVA were conducted. The first test proceeded to calculate the general
effects, while the second one tested the impact on each PES item separately. As represented
in Table 2, the results of the multivariate analysis showed a significant effect of the activity
of the day (Group: Agrit/Routine) on PES (Pillai’s trace = 0.496, pvalue = 0.001). It implies
that the effect size of the day’s activity on improved mood is 0.496, or in other words, 49%
of the PES’s variation is determined by the activity of the day. Moreover, the ANOVA test
showed significant effects of the variable Group on all the items of PES; thus, the Pillai’s
traces are acceptable.
Table 2.
Evaluating the effects of different factors on PES based on the multivariate and univariate
analysis of variance.
Multivariate Analysis Univariate Analysis
PES 1 PES 2 PES 3 PES 4
Effect Pillai’s Trace pη2pη2pη2pη2p
Group * 0.496
<0.001
0.261
<0.001
0.306
<0.001
0.397
<0.001
0.252
<0.001
Gender 0.018 0.511 0.003 0.491
<0.001
0.924 0.001 0.677 0.009 0.185
Age 0.192 0.116 0.029 0.597 0.076 0.037 0.06 0.115 0.035 0.467
WB 0.078 0.005 0.028 0.022 0.041 0.005 0.057 0.001 0.015 0.092
ST 0.038 0.131 0.002 0.581 0.028 0.022 0.006 0.293 0.007 0.261
* Group: represent the activity of the day (Agrit/Routine). η2: Partial Eta Squared. p:p-value.
Multivariate and univariate analyses were performed for WB and ST to test if the
participants’ well-being and stress levels could contribute to their improved mood. A
significant effect was detected between WB and PES (Pillai’s trace = 0.078, pvalue = 0.005).
In other words, the effect size of WB on PES was 0.078, and it accounted for 78% of PES’s
variation. Besides, univariate analysis revealed that there is a significant effect of WB on
three PES items. The p-value for the fourth item is borderline (pvalue = 0.092), which is
considerable (Table 2).
However, the p-value was insignificant for ST, gender, and age. Therefore, the stress
level of the participants and the mentioned demographic criteria have no effects on PES.
Given that the variables Group and WB have a significant effect on PES, the multiple
linear regression method was performed to identify the ‘strength’ of the mentioned effects.
The Routine-group was considered the baseline for the Agrit-group in testing the strength.
The result revealed a significant ‘difference’ between the effect of agritourism-experience
Sustainability 2021,13, 8712 9 of 16
and routine activity on PES. In fact, those participants who experienced agritourism scored
the PES items higher than the control group, with significant p-values (Beta = 1.076, 1.229,
1.519, 0.955 for items 1 to 4, respectively) (Table 3). For instance, for PES 1, the beta
score implies that the Agrit-group participants scored 1.076 higher than the control group
participants.
Table 3. Using multiple linear regressions to estimating the regression coefficient (beta) of variables on PES items.
PES 1 PES 2 PES 3 PES 4
B (95% CI) pValue B (95% CI) pValue B (95% CI) pValue B (95% CI) pValue
Agrit-group 1.076 (0.813, 1.339) <0.001 1.229 (0.96, 1.497) <0.001 1.519 (1.247, 1.79) <0.001 0.955 (0.716, 1.194) <0.001
Gender Male 0.089 (−0.165, 0.342) 0.491 −0.013 (−0.271,
0.246) 0.924 0.055 (−0.206,
0.317) 0.677 −0.155 (−0.385,
0.075) 0.185
Age
<20 −0.253 (−1.01, 0.504) 0.51 0.031 (−0.742,
0.803) 0.938 −0.506 (−1.286,
0.274) 0.202 −0.149 (−0.836,
0.539) 0.67
21–30 −0.327 (−1.05, 0.395) 0.372 0.073 (−0.665, 0.81) 0.846 −0.544 (−1.289,
0.201) 0.151 0.008 (−0.648,
0.665) 0.98
31–40 −0.112 (−0.828, 0.604) 0.758 0.095 (−0.636,
0.826) 0.798 −0.171 (−0.909,
0.567) 0.648 0.23 (−0.42, 0.88) 0.486
41–50 −0.184 (−0.911, 0.543) 0.618 −0.259 (−1.001,
0.483) 0.491 −0.415 (−1.165,
0.334) 0.276 0.093 (−0.568,
0.753) 0.782
51–60 −0.118 (−0.91, 0.673) 0.769 0.658 (−0.15, 1.466) 0.11 −0.405 (−1.222,
0.411) 0.329 0.15 (−0.569, 0.869) 0.682
61–70 0.054 (−1.051, 1.16) 0.923 0.38 (−0.748, 1.509) 0.507 0.703 (−0.437,
1.843) 0.225 0.503 (−0.501,
1.508) 0.324
>71 0.915 (−0.501, 2.33) 0.204 −0.638 (−2.083,
0.807) 0.385 −0.244 (−1.703,
1.216) 0.742 0.541 (−0.744,
1.827) 0.407
WB 0.043 (0.006, 0.079) 0.022 0.053 (0.016, 0.091) 0.005 0.064 (0.026, 0.102) 0.001 0.029 (−0.005,
0.062) 0.092
ST −0.004 (−0.018, 0.01) 0.581 0.017 (0.002, 0.031) 0.022 0.008 (−0.007,
0.022) 0.293 0.007 (−0.005, 0.02) 0.261
R20.34 0.40 0.50 0.32
Adjusted R20.30 0.36 0.47 0.28
B: Beta: Regression coefficient; CI: Confidence interval. The Routine group, female, age less than the previous levels were considered as the
reference levels.
For testing the strength of the WB score on PES though, the calculation was different.
First, we calculated the individual score of wellbeing for each participant based on the
‘WHO wellbeing test’ [
31
]. After that, multiple linear regression tests were performed to
estimate how the wellbeing score changes affected PES scores. The presented beta for the
effect of WB on PES in Table 3shows that, with a one-point increase in the total wellbeing
score, the score of PES-1 increased by an average of 0.043 (pvalue = 0.022). Such an effect
was significant in other items with a regression coefficient of 0.053, 0.064, and 0.029. It
implies a significant correlation between WB and PES, in which a higher wellbeing score
can increase the PES score.
Having nominal regression coefficients for ST, age, and gender, it can be claimed that
the changes within these factors will not predict PES scores.
Additionally, four items of PES were combined and computed to form a merged
variable of total PES. Multiple linear regressions were conducted to estimate whether the
involved variables will have similar effects on total PES. The result showed a significant
effect of the group (Agrit/routine) on total PES (Partial Eta Squared = 0.493, pvalue = 0.001),
and WB effect on total PES (Partial Eta Squared = 0.072, pvalue = 0.001). These two variables
can potentially estimate the changes in total PES.
As in the reported results in Table 3, once again, the routine-group was considered the
baseline. The differences between the Agrit-group and control groups were tested in terms
of the score of total PES. As shown in Table 4, the reported PES by Agrit-group participants
was averagely 4.779 units higher than the Routine-group (pvalue = 0.001). Besides, an
increase in the ‘total WB score’ led to an increase in the perceived total PES by an average
of 0.189 units (p-value = 0.001).
Sustainability 2021,13, 8712 10 of 16
Table 4.
Using multiple linear regressions to estimating the regression coefficient of variables on
total PES.
Parameter B (95% CI) pValue
Gender Male −0.024 (−0.676,
0.628) 0.943
age
<20 −0.877 (−2.824, 1.07) 0.377
21–30 −0.791 (−2.65, 1.069) 0.405
31–40 0.042 (−1.8, 1.884) 0.964
41–50 −0.766 (−2.636,
1.104) 0.422
51–60 0.285 (−1.752, 2.322) 0.784
61–70 1.641 (−1.204, 4.486) 0.258
>71 0.574 (−3.068, 4.217) 0.757
Agrit-group 4.779 (4.102, 5.456) <0.001
WB 0.189 (0.094, 0.283) <0.001
ST 0.028 (−0.008, 0.063) 0.130
R20.57
Adjusted R20.55
B: Beta: Regression coefficient; CI: Confidence interval. The Routine group, female, age less than the previous
levels were considered as the reference levels.
3.3. Testing the Interactions
The final analysis estimated, the potential combined effects of the self-reported vari-
ables and the activity of the day. PES was considered a dependent variable. It was
conducted by testing the effect of interactions in multiple linear regression models. Prior to
calculating the interactions’ effect, the Pearson correlations were analysed, and only the
variables with significant correlations were involved in the interaction tests.
Testing the interaction effects on PES shows that significant interaction may arise
when considering the relationship between self-reported wellbeing and agritourism with
beta = 0.239, pvalue = 0.014 (Table 5).
Table 5.
Evaluating the interaction between the Agrit-group and wellbeing on total PES base on
multiple linear regression.
Dependent Variable: PES
Parameter Beta (95% CI) pValue
Intercept 10.267 (7.850, 12.685) 0.000
Agrit-group * 0.208 (−3.359, 3.776) 0.908
Wellbeing 0.070 (−0.066, 0.205) 0.311
Interaction of Agrit-group *
and wellbeing 0.239 (0.049, 0.429) 0.014
* In comparison to the Routine group.
The results of the correlations and interactions tests are presented visually in
Figure 1
.
It is clear that participation in agritourism and reported wellbeing can increase PES com-
pared to the control group. Perceived PES was higher for Agrit-group members after
spending a day on the farm and having agritourism activities (Figure 1A). In other words,
the interaction of the reported wellbeing and agritourism has a combined effect on im-
proved mood.
Sustainability 2021,13, 8712 11 of 16
Sustainability 2021, 13, x FOR PEER REVIEW 11 of 16
3.3. Testing the Interactions
The final analysis estimated, the potential combined effects of the self-reported var-
iables and the activity of the day. PES was considered a dependent variable. It was con-
ducted by testing the effect of interactions in multiple linear regression models. Prior to
calculating the interactions’ effect, the Pearson correlations were analysed, and only the
variables with significant correlations were involved in the interaction tests.
Testing the interaction effects on PES shows that significant interaction may arise
when considering the relationship between self-reported wellbeing and agritourism with
beta = 0.239, p value = 0.014 (Table 5).
Table 5. Evaluating the interaction between the Agrit-group and wellbeing on total PES base on
multiple linear regression.
Dependent Variable: PES
Parameter Beta (95% CI) p Value
Intercept 10.267 (7.850, 12.685) 0.000
Agrit-group * 0.208 (−3.359, 3.776) 0.908
Wellbeing 0.070 (−0.066, 0.205) 0.311
Interaction of Agrit-group * and wellbeing 0.239 (0.049, 0.429) 0.014
* In comparison to the Routine group.
The results of the correlations and interactions tests are presented visually in Figure 1. It
is clear that participation in agritourism and reported wellbeing can increase PES compared
to the control group. Perceived PES was higher for Agrit-group members after spending a
day on the farm and having agritourism activities (Figure 1A). In other words, the interaction
of the reported wellbeing and agritourism has a combined effect on improved mood.
For the stress level, though, the parallel lines in Figure 1B represent no interaction
effect of the reported stress level and the activity of the day on the PES.
Figure 1. The correlation and interaction of wellbeing (A) and stress (B), with the activity of the day, on the total PES.
4. Discussion
This paper studied agritourism as a new possibility for engaging in green space and
the outdoors to improve wellbeing. The focus was on agritourism activities and its po-
tential benefits on mental health, specifically the psychological aspects and its features in
South Korea. The first strength of this study relates to the positive impact of agritourism
activities on the perceived improvement of physiological health. Furthermore, the results
are consistent with similar studies for experiences in a public green space or nature
tracking activities [1,35,66].
First, we provide additional validation of the positive outcomes of green space ex-
posure in terms of mental health. We show that agritourists perceived a considerable
improvement in their immediate mood compared to the control group who stayed at
Figure 1. The correlation and interaction of wellbeing (A) and stress (B), with the activity of the day, on the total PES.
For the stress level, though, the parallel lines in Figure 1B represent no interaction
effect of the reported stress level and the activity of the day on the PES.
4. Discussion
This paper studied agritourism as a new possibility for engaging in green space
and the outdoors to improve wellbeing. The focus was on agritourism activities and its
potential benefits on mental health, specifically the psychological aspects and its features
in South Korea. The first strength of this study relates to the positive impact of agritourism
activities on the perceived improvement of physiological health. Furthermore, the results
are consistent with similar studies for experiences in a public green space or nature tracking
activities [1,35,66].
First, we provide additional validation of the positive outcomes of green space ex-
posure in terms of mental health. We show that agritourists perceived a considerable
improvement in their immediate mood compared to the control group who stayed at home.
It was claimed that engaging in outdoor and adventure activities will lead to positive
outcomes, such as the reported improved mood after walking on a green path [
12
,
66
]. Our
study adds to this claim and reports that, after the agritourism experience, the increase
in the improved mood was significantly higher for the experimental group than for the
control group. Such significant differences in the perception of PES between the Agrit
and Routine group adhere to the theory in which it was claimed that the “immediate
social or physical environment” can influence personal perceptions [
67
]. However, several
other factors might contribute to such a mood change after green-space exposure. For
example, Bradley and Inglis (2012) argued that, in order to facilitate positive development
and personal growth among the participants, leisure activities are better designed to be
challenging and in a way that requires effort and skills [
68
]. Likewise, it was reported
that increasing activity levels during hiking in nature could effectively improve health
and wellbeing indicators [
1
]. In terms of agritourism, the weather, companions, level of
engagement in the activity, and the nature of the activity might affect the outcomes as
confounding variables. So, we tried to select homogenised sites and samples in this study.
Nevertheless, our findings are consistent with research in a school project crossing the
ALPs [
35
]. They pointed out that outdoor and adventure programs play an essential role
in improving subjective wellbeing. Furthermore, they proved that such activities might
reduce feelings of time pressure and mental stress. Moreover, a comparison between two
gardening activities and reading showed that positive mood was significantly higher after
gardening [4].
Second, having self-reported measures of stress and wellbeing, we found several
interesting patterns in the data. Our findings affirm that the participants’ well-being
perceptions can contribute to their agritourism experience and its associated outcomes.
However, the findings do not lend any credence to such a contribution in terms of stress.
Despite the fact that stress levels have been associated with green-based activities in other
research [
13
,
44
]. Hence, such a result might suggest that agritourism experience may be
related to the ‘perceived stress’ through different mechanisms.
Sustainability 2021,13, 8712 12 of 16
Finally, a significant interaction was found between self-reported wellbeing and
agritourism and a combined effect on improved mood. Accordingly, it seems that the
positive mental health outcomes of agritourism can be increased with a higher perception of
wellbeing. It was reported that a lower perception of wellbeing is attributed to depression
and stress, whereas high levels are associated with enjoyment and happiness [
69
]. The
result of the positive interaction between WB and agritourism adds to this claim.
4.1. Limitations
Though this study expands the existing knowledge base about the mental health
outcomes of green-spaces exposure and literature, there are several limitations, and oppor-
tunities for further research remain.
First, the causal relationship is not easy to conclude due to various confounding vari-
ables in the social environment. Time-lagged designs are likely to provide some evidence
for temporal causality; however, it is impossible to make assumptions of causality [
69
].
This study tried to report the potential relationship and not the order of causality among
the involved variables.
Second, the variables of psychological health were measured based on self-reported
data, which might cause bias. However, we applied standard measurement tools, and a
detailed description of the study process is provided.
Third, it has been suggested to involve more demographic criteria and test them as
control variables since the changes in the type of personal and environmental exposure to
green space might impact the results [
49
]. Future research can involve control variables
to ascertain whether they change the effects of agritourism on mental health. However, it
is suggested that including standardised quantitative data collection methods will better
understand the underlying factors [
49
]. Therefore, we applied this remedy to increase the
credibility of the result.
Likewise, several confounding factors (from personal, social, and environmental
aspects) might play a role in mediating the health effects of green space, and generalisations
might not be accurate. For example, it is believed that both quantity and quality is important
in terms of the outcomes of green-based activities [
35
,
44
], or population subgroups may
benefit differently from exposure to green space, or a designed trend of intervention can
be affected by environmental factors [
49
]. In fact, it is not clear if the improved mood is
related to other confounding factors rather than the presence of the agritourism site. Even
though some co-exposure factors were considered during the visit (such as duration of
visit, environment, activities undertaken, and subjective feeling), various other factors
could potentially mediate the results.
As a remedy for this main bias, randomisation was conducted to adjust some con-
founding variables on the selected participants in both groups. Randomisation can reduce
selection bias and is a standard research design feature. We also tried to select similar
agritourism sites to ensure participants’ exposure to somehow similar environments and
activities.
Fifth, it is not clear whether the beneficial health outcomes of agritourism were a
short-term effect on mood or if they could last for a long time.
Testing the proposed relationships through cross-national data in future studies would
present a picture of whether agritourists in different countries report the same outcomes of
agritourism activities or not.
4.2. Practical Suggestions for Agritourism Development
The implications of this study are important to both policymakers and planners and to
the owners of agritourism sites. We stress the need to promote agritourism sites, which can
potentially lead to increased mental health in society. Such promotion can be implemented
through three main policies: (1) raising the awareness on the mental health outcomes of
agritourism, (2) encouraging people to visit and experience agritourism, (3) and designing
the provided activities in a way that can evoke the visitors’ psychological health.
Sustainability 2021,13, 8712 13 of 16
To promote agritourism site visits, planners need to ensure that agritourism activities
can address the needs of a broad range of visitors. Attention to biodiversity can be
helpful [
30
]. Still, it is far more essential to design the activities and environment to
motivate visitors from different social groups to visit and extend the length of their stay.
Pre-organised and well-established events are required to increase the opportunities for
engaging visitors in different activities. In practice that means encouraging visitors to
engage in activities can potentially provide more opportunities for them to have nature-
based coping strategies in their stressful lifestyles in cities. The spiritual outcomes would
be through nature contacts and challenging activities, while the social outcomes would be
through interactions in group activities. Likewise, attention to landscape designing might
evoke satisfaction and assist mood-boosting, since it is believed that the landscape can
promote mental, physical, and social wellbeing [70].
In order to raise awareness about the psychological benefits of agritourism in society,
information can be imparted to the community via the national websites of both tourism
services and of the health industry that connect outdoor activities with mental health
outcomes. Moreover, designing child-appropriate activities will attract the attention of
the whole family. The CDC’s organisation emphasised encouraging children to engage
in healthy outdoor activity and the critical role of communities, schools, and families in
promoting such activities. In addition, agritourism programs can be integrated into the
school curriculum, and the benefits of such a unique outdoor activity also can be stressed
by pediatric health care providers [
46
]. Another practical suggestion is to engage school
pupils in choosing some organic products for their school dining [23].
5. Conclusions
It can be concluded from the findings that visiting agritourism sites and engaging in
the associated activities can improve the perceived immediate mood. In addition, perceived
wellbeing might contribute to such immediate mood-boosting. There is a combined effect
and positive outcomes of the interaction between wellbeing and agritourism. Therefore, it
seems that agritourism as an emerging green-based activity can potentially contribute to
improving mental health. The results add to a growing body of knowledge on the positive
effects of green-space exposure on mental health. That body of knowledge is growing
worldwide from Finland to Australia, not only in South Korea [71,72].
Author Contributions:
Conceptualization, M.R., L.R. and D.K.; methodology, A.A.; software, M.R.
and A.A.; validation, L.R., D.K. and A.A.; formal analysis, A.A.; investigation, L.R. and M.R.;
resources, L.R. and M.R.; data curation, L.R. and M.R.; writing—original draft preparation, L.R.;
writing—review and editing, L.R.; visualization, A.A.; supervision, L.R. All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Acknowledgments: This paper was supported by the KU Research Program of Konkuk University.
Conflicts of Interest: The authors declare that they have no competing interests.
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