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Background:
Systematic Review

Psychological Effects of Green Experiences in a Virtual Environment: A Systematic Review

by
Mijin Lee
,
Eunsoo Kim
,
Jiwon Choe
,
Seonhye Choi
,
Siyeon Ha
and
Geonwoo Kim
*
Forest Human Service Division, Future Forest Strategy Department, National Institute of Forest Science, Seoul 02455, Korea
*
Author to whom correspondence should be addressed.
Forests 2022, 13(10), 1625; https://doi.org/10.3390/f13101625
Submission received: 2 September 2022 / Revised: 19 September 2022 / Accepted: 27 September 2022 / Published: 3 October 2022
(This article belongs to the Special Issue The Healing Power of Forests)
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Abstract

:
As mental health issues increase worldwide, nature-based experiences are being recognized as alternative treatments for improving health and well-being. Increasing urbanization precludes many people from accessing green spaces owing to time or physical limitations. Therefore, opportunities to connect with nature through virtual technology is being encouraged. We conducted a systematic review of studies on the psychological effects of experiencing nature using virtual technology. We searched the academic databases PubMed, Web of Science, and Scopus for relevant studies and assessed their quality using Cochrane’s RoB 2 and ROBINS-I tools. Twenty-one studies were included and the psychological outcomes were negatively synthesized by the intervention characteristics (duration, observation position of the landscape, interaction, environment description, and sensory type). Psychological outcomes were classified into emotional recovery, cognitive recovery, stress reduction, and other indicators. Emotional recovery was most consistently presented, and virtual natural contact alleviated negative emotions more than it elicited positive emotions. Additionally, virtual nature interventions lasting more than 10 min showed more consistent effects than those of less than 10 min. Moreover, an open field of view led to significant emotional recovery and an in-forest view led to significant cognitive recovery. Despite some limitations, our findings will contribute to the development of virtual forest experiences to improve human well-being.

1. Introduction

Since the global COVID-19 pandemic, many people have experienced difficulties, including anxiety about infection, employment instability, financial pressures, and social isolation [1,2]. The implementation of social distancing to prevent the spread of disease resulted in many social contact activities moving to online platforms [3]. Office workers have increased contact-free meetings and working from home [4,5], and students conduct classes through distance education [6,7]. In addition, leisure activities had to be performed alone or with only a few people, and the demand for over-the-top (OTT) services using media platforms such as Netflix, Disney Plus, and YouTube has exploded [8,9]. Personal and social problems arose as contact between people gradually diminished and feelings of isolation increased [10,11,12]. In particular, compared to before COVID-19, anxiety and depression increased worldwide by 25.6% and 27.6%, respectively [13], and mental health problems and solutions are receiving more attention.
There is increasing evidence that experiences in the natural environment have a positive effect on health [14,15,16]. Forest immersions have been studied as alternatives to therapy for improving physical and mental health and are receiving greater attention as more people visit green spaces after the pandemic [17,18,19,20]. Appreciating the forest or walking improves mood, reduces depression and anxiety [21,22], and relieves stress after forest bathing [23]. However, as urbanization progresses in many countries, accessibility is one of the most influential and limiting factors for visiting forests [24], and there may be transportation, time, and physical challenges to accessing forests or other green environments. Therefore, some people do not have the opportunity to enjoy the benefits of forests and green environments.
One way in which many people can access nature without temporal and spatial limitations is through the use of virtual reality (VR) [25,26]. Studies have reported the effects of diagnosis, rehabilitation, and learning using VR in various fields such as medical care, health care, and education [27,28,29]. Virtual technology can be used in special situations because it has the advantage of being controllable [30]. In addition, studies have been conducted on health, well-being, and education through VR in forests. Wang et al. [31] conducted a study on stress according to the type of virtual forest environment, and Annerstedt et al. [32] reported the effect of the presence or absence of sound in a virtual forest. Zimmerman et al. [33] evaluated learning ability after identifying trees, plants, and ecosystems by applying augmented reality (AR) to children.
Recently, systematic reviews have reported that studies on interventions to virtually experience nature have increased. For example, Jo et al. [34] conducted a comprehensive review of the physiological effects of natural elements that can be observed indoors, including photos, videos, and VR, and Syed Abdullah et al. [35] conducted a systematic review of the effects of virtual natural therapy using VR on stress. Previous reviews have included all visual interventions of natural elements or performed a systematic review of stress among the psychological effects of interventions using VR. However, no review has specifically focused on the psychological effects of the intervention program classification, including both VR and other virtual technologies. The expectation that the use of virtual technology in forests will increase with technological development is essential for a systematic review of the psychological effects of virtual green experiences.
Therefore, in this study, we conducted a systematic review of studies that investigated the psychological effects of green environments using virtual technologies such as VR or 3D technology. As a result, this study investigated the categorization of the intervention program and the types of psychological indicators, and specifically analyzed the results and psychological indicators for the duration, landscape, and characteristics of the intervention program. In this regard, we intend to provide basic data on the psychological effects of virtual green environments. Additionally, we anticipate that this study will contribute to the development of strategies for using virtual forests to increase the quality of life for people with mental and physical disabilities as well as healthy people.

2. Materials and Methods

2.1. Protocol and Registration

This review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [36,37]. This systematic review was registered on the PROSPERO (CRD42022324834) and OSF databases (DOI:10.17605/OSF.IO/VRBDW) prior to commencing.

2.2. PICOS and Eligibility Criteria

The research question was set by specifying the population, intervention, comparison, outcome, and study design (PICOS) (Table 1). Before study selection, we established eligibility criteria following the PICOS framework. Supplemental Table S1 reports the PRISMA checklist used for this review.

2.3. Search Strategy

This review used previous systematic reviews on virtual and green-based interventions to develop keywords for searching relevant studies and obtaining reproducible search results [34,35,38,39]. This review did not use keywords for participants or comparators to collect all relevant studies on virtual green-based interventions. Therefore, search keywords were selected to identify interventions, outcomes, and study designs (Table 2). Three databases were searched: PubMed, Web of Science, and Scopus, and all studies published in English before March 2022 were included in the search.

2.4. Study Selection

From the database search, a total of 3201 studies were found with 785 on PubMed, 742 on Web of Science, and 1674 on Scopus. The search results were exported to the EndNote citation manager software (EndNote X9.3.3, Clarivate Analytics, London, UK), and 502 duplicates were removed. The authors reviewed the titles and abstracts of 2699 publications and removed 2436 articles because of explicitly irrelevant cases. Subsequently, two authors (M.L. and J.C.) independently screened the full text of 263 studies, and any disagreements were resolved by two other authors (S.H. and G.K).
Nineteen studies met the eligibility criteria for inclusion. Two additional studies that met the eligibility criteria were included after reviewing the references of the searched studies. Therefore, a total of 21 studies were selected for review (Figure 1).

2.5. Data Extraction

Two authors (E.K. and S.C.) independently used the same data extraction method to ensure a precise and unbiased process. The following data were extracted from each study: study information (first author, year of publication, and country), sample (participant characteristics, sample size, gender, and age), intervention (activities, duration, characteristics, and virtual equipment), outcome (psychological measurement indicators, and significance), control group, study design, and presence of pre-registration of the study (e.g., protocol; IRB).

2.6. Narrative Synthesis

In this review, a narrative synthesis of intervention characteristics was conducted. We calculated the ratio of significant psychological outcomes in each category as described by Mygind et al. [40]. A qualitative synthesis was conducted using 33 intervention programs conducted in the 21 studies included in the final selection. The synthesis was categorized according to the characteristics of the intervention program, and the significant outcomes were identified. Subsequently, the percentage of significant positive effects on a psychological outcome (%p) and the percentage of both significant positive effects and non-significant positive effects on a psychological outcome (%p + m) were calculated. The results for each category were then compared.

2.7. Methodological Quality Assessment

This review did not impose strict restrictions on the study design to ensure that all relevant studies on the psychological effects of green experiences in a virtual environment were included. We used two methodological assessment tools based on the study design. ROBINS-I was used to evaluate NRCT (non-randomized controlled trials) studies, and RoB 2 was used to evaluate RCT (randomized controlled trials) studies, according to the recommendations of the Cochrane Handbook [36,41]. Two authors (M.L. and J.C.) independently assessed the risk of bias and the results were expressed using Review Manage software (RevMan 5.4, Cochrane Collaboration, Oxford, UK).
RoB 2 was structured into five domains: (1) bias arising from the randomization process, (2) bias due to deviations from intended interventions, (3) bias due to missing outcome data, (4) bias in the measurement of the outcome, and (5) bias in the selection of the reported result. Each domain was evaluated on three levels: “low risk”, “some concerns”, and “high risk”. The highest risk across the five domains was recorded as the overall risk level.
ROBINS-I was structured into seven domains: (1) bias due to confounding, (2) bias in the selection of participants for the study, (3) bias in the classification of interventions, (4) bias due to deviations from intended interventions, (5) bias due to missing data, (6) bias in measurement of outcomes, and (7) bias in the selection of the reported result. Each domain was evaluated on five levels of risk to bias: “low risk”, “moderate risk”, “serious risk”, “critical risk”, and “no information”.

3. Results

3.1. Study Characteristics

A total of 21 studies were included in this systematic review, and the characteristics of the studies are shown in Table 3. The total number of participants in the 21 studies was 1325, and the number of participants in each study ranged from 13 to 189. In the demographic review, 18 studies were performed on young adults and there was one study each on elementary school students, 50–75-year-olds, and the elderly (60 years or older). The special subjects were people with mild depression and anxiety disorders in three studies and one study on chronic pain.
The intervention program was conducted in green environments such as forests, parks, lawns, and trees through a virtual environment, and one session was performed in all studies. The intervention time ranged from 3 to 20 min, with an average of 8 min 30 s, and a median of 9 min 50 s. There were 10 studies with sessions lasting more than 10 min and 11 studies with sessions of less than 10 min. In the classifications where participants were located in an in-forest (near view) and an open-view (distant view) scenario, there were 14 in-forest and seven open-view studies. In addition, eight studies explored the virtual environment through interactive activities, such as games and walking, and fourteen studies focused on appreciation. The virtual environment was depicted artificially in 12 studies and conducted in a filmed real natural environment in 10 studies. Regarding the use of senses, seven studies did not mention other senses except for sight, whereas fourteen studies included hearing, smell, or touch senses as well as sight. Most of the research was conducted with VR (virtual reality) and 360-degree video, and IVE (immersive virtual environments) and 3D were used in some studies. We investigated the outcomes according to the five intervention characteristics categorized above (Table 4).
As a result, 29 indicators were used, and the main measurements were divided into emotional recovery (positive and negative), cognitive recovery, and stress. Indicators were measured in terms of both positive and negative (fourteen studies), positive (one study), negative (three studies), cognitive recovery (six studies), and stress (five studies). Other indicators included presence (two studies), self-esteem (one study), self-efficacy (one study), pain scale (two studies), and natural relevance and independence (two studies).
The study design consisted of randomized controlled trials (fourteen studies), randomized crossover trials (three studies), and non-randomized controlled trials (four studies). The study was conducted in 10 countries including the United States (four studies), Taiwan (three studies), China (three studies), Finland (two studies), Korea (two studies), Germany (two studies), Australia (two studies), Canada (one study), Singapore (one study), and the UK (one study). Of the 21 studies, 17 were conducted after 2020, and one study each was conducted in 2010, 2015, 2017, and 2018.

3.2. Categorized Intervention

Of the 21 studies included in the review, 33 interventions were performed. The characteristics of the intervention program were classified into five categories. These were the duration of the intervention program, the observation position of the virtual environment, the interaction with the virtual reality, the restoration method of the virtual environment, and the type of sense (Table 4). The results of the psychological indicators were analyzed according to the characteristics of the intervention program.
As a result of classification according to intervention duration, 10 studies were conducted for more than 10 min and 11 studies were conducted for less than 10 min. In all categories, there were significant results (%p) and positive effects (%p + m) for durations of 10 min or longer. As for the observation position item, 14 in-forest studies and seven open-view studies were included. Cognitive recovery was particularly significant in the in-forest studies. In the interaction classification, there were eight interaction and 14 non-interaction studies, and emotional recovery and stress were effectively measured in the interaction studies. The environment description was depicted artificially in 12 studies and conducted using a filmed real environment in 10 studies. Lastly, in the sensory type, seven studies only used sight and fourteen studies included other senses in addition to sight.
Regarding the indicator, it was found that emotional recovery was significant in more than 50% (%p) of studies, and significant effect and non-significant positive effects in more than 80% of studies (%p + m). Moreover, a significant effect was found for the alleviation of negative emotions rather than positive emotions being elicited for all indicators. Cognitive restoration was particularly effective in the in-forest studies.

3.3. Outcomes

3.3.1. Emotional Restoration

In this review, most studies investigated the indicators of emotional restoration. Therefore, emotional restoration was classified into positive and negative emotions. Positive emotions included the positive effect as defined in PANAS and ZIPERS, positive effect and serenity in PANAS-X, vigor and friendliness and total in POMS, calmness and happiness and positive effects in VAS, and SVS. Negative emotions included the negative effects defined in PANAS, PANAS-X, and ZIPERS, depression, tension, anger, fatigue, and confusion in POMS, and insecurity of VAS, STAI, and STADI.

Positive Emotion

Fourteen studies reported the restoration of positive emotions. For classification according to the control group, the control group was set as the city in nine studies, which compared an urban environment with a green environment [44,45,48,51,52,55,56,58,60]. The study that selected the city as a single control had the most shopping malls, subways, buildings, and crowd. As a result, the positive emotions of the group that appreciated nature rather than the city showed significant positive effects [44,45,51,56,58,60]. Mostajeran et al. [48] reported that the total POMS score was significant in the 360-degree virtual environment when the urban 360-degree virtual environment, urban slideshow, and natural slideshows were used as a control group. Jo et al. [52] compared urban commercial areas to coastal and forest groups and found that the vitality, total score, and friendliness of POMS were significantly increased. Newman et al. [55] conducted two studies; in the first, when comparing the group that watched the real-forest and 2D video with the VR group, the positive effect was not significant, but serenity was significantly affected. Subsequently, the second study was conducted on virtual nature with high or low realism, using a virtual city with high or low realism as the comparison group. Significant results were reported for positive effects and serenity.
In three studies, real and virtual forests were compared [42,57,61]. Emamjomeh et al. [42] used a forest seen through a window in virtual reality and a forest viewed through a real window, and a real office or a virtual office. It was reported that positive emotions were not significantly affected, but they did recover. In two other studies, it was found that the recovery of positive emotions when observing a VR forest was not significant when compared to the group that observed a real forest [57,61].
Two further studies compared a control group (an abstract slideshow or place without plants) and an experimental group (with green plants in yards or forests) [47,59]. In both studies, the positive effects measured by ZIPERS significantly increased.

Negative Emotion

A total of 18 studies reported the alleviation of negative emotions. Over half of the studies showed that the alleviation of negative emotions was effective, and 13 studies reported that the experience of a green environment in virtual reality effectively alleviated negative emotions [42,44,49,50,51,53,55,56,57,59,60,61,62]. In the study by Yin et al. [53], viewing the scenery outside the window or a combination of the outside the window and green plants observed indoors significantly reduced anxiety more than when green plants were observed indoors. Schebella et al. [56] also studied the effectiveness of low, medium, and high levels of biodiversity in the field. They found that instability and anxiety were alleviated at all three levels, and anxiety in particular was significantly relieved in the low-biodiversity group.
In two studies, negative emotions were alleviated after experiencing the virtual forest through movement; however, this was not significant [47,58].
Three studies in which participants viewed forests filmed in a fixed location measured negative emotions using POMS [45,48,52]. Fatigue had a significant effect in all three studies. Tension and confusion significantly alleviated in studies [45] and [52], and it was reported that depression and anger showed significant effects in one study each.

3.3.2. Cognitive Restoration

Six studies investigated cognitive restoration after experiencing a virtual environment [42,43,45,47,57,61]. Cognitive fatigue was measured using the Restoration Outcome Scale (ROS), Restorative Components Scale (RCS), Perceived Restorativeness Scale (PRS), and Sustained Attention to Response Test (SART). Cognitive function was measured using working memory, problem-solving ability, and mathematics quizzes.
Two studies reported changes in cognitive fatigue after a virtual environment experience [45,57]; after the participants experienced the forest filmed at a fixed location, the recovery of cognition significantly increased in the forest group compared with the non-forest group.
Another three studies measured cognitive function [42,47,61] and reported that the participant’s ability to solve mathematical problems or complete memory tests increased after a virtual environment experience but was insignificant.
One study examined cognitive fatigue and cognitive function when experiencing a virtual forest during break time in elementary school students [43]. The results showed that the ROS showed a significant average difference compared to a general break time or no break time, but there was an insignificant effect on problem-solving ability between the groups.

3.3.3. Stress

Five studies investigated stress [42,49,56,60,62] and used the Short Stress State Questionnaire (SSSQ), Standard Stress Scale (SSS), Perceived Stress Scale (PSS), and Visual Analog Scale (VAS).
Three studies investigated changes in stress when experiencing virtual environments, including interactions [49,60,62]. Reese et al. [49] measured stress after exploring a virtual environment created to resemble a real forest. The group that experienced walking in this virtual environment showed a decrease in stress, similar to the group that experienced walking in a real-life natural environment. However, there was no significant effect on stress owing to the small to medium effect size. Chan et al. [60] conducted a study in which the elderly walked in a virtual environment according to hand movements. This study found that although not statistically significant, stress increased slightly in the urban group and decreased in the forest group. Wang et al. [62] investigated the stress of exercise in a virtual environment in people aged 50–75 with anxiety disorders. The group who rode a bicycle for 20 min in a virtual nature environment had significantly reduced stress than the group who rode a bicycle while looking at abstract paintings.
Two studies investigated the changes in stress when experiencing a virtual environment in a fixed place without interaction [48,56]. Mostajeran et al. [48] did not find a significant effect on stress when watching three 2 min videos in a row. Schebella et al. [56] measured these effects according to the degree of biodiversity, olfaction, and hearing. The stress-reduction effect was more significant in the low-biodiversity group than in the urban environment group. Although stress was reduced in the medium- and high-biodiversity groups, the effect was not significant.

3.3.4. Other Effects

Eight studies evaluated presence indicators, self-efficacy, self-esteem, pain scales, and independence or connection to nature, in addition to emotion, cognition, and stress. Among them, the Igroup Presence Questionnaire (IPQ) was used to measure perceived presence during the virtual environment experience [42,48]. The IPQ includes general and spatial presence, involvement, and realness. Mostajeran et al. [48] found that 360-degree videos had a significantly higher presence than slideshows do. In particular, the study emphasized that spatial presence and involvement are more prevalent in forest environments than in urban environments. In one study, general presence was found to be significant [42].
One study reported the effect of a virtual environment on self-esteem [44] and found that self-esteem significantly decreased in the group that viewed the city but increased in the group that viewed natural environments such as forests or waterfalls.
One study measured self-efficacy according to the appreciation of or interaction with a virtual environment [51]. This study included activities such as appreciation, interaction, fishing, and watering the garden. The results showed that self-efficacy increased in all groups and significant effects were found in the appreciation and fishing groups.
Two studies investigated the effects of pain scales in virtual environments [46,50]. Gromala et al. [46] provided an environment for adults with chronic pain to walk through a virtual forest. There was a noticeable decrease in pain, whereas the mindfulness-based stress reduction (MBSR) control group reported little change. Another study found that after exposure to stress, the group that rested while taking in virtual nature had significantly decreased pain compared to the group that received biofeedback [50].
Two studies reported a relationship and independence with nature after walking in a virtual forest [54,60]. Sneed et al. [54] conducted a study using videos captured while walking in a real environment for 10 min. Consequently, the Nature Relatedness Scale (NRS) was increased in the group that walked through the real and virtual forests, but the group that observed a virtual library experienced little change. The change in the forest group was significant when comparing the NRS to the library group. In addition, as a result of the State of Independence with Nature Scale (SINS), the library group significantly decreased, whereas the forest environment group significantly increased. Another study measured connection with nature using the Connectedness to Nature Scale (CNS) [60]. This study was conducted on young adults and the elderly, and the scale of connection with nature significantly increased when participants experienced a nature-based environment compared with the urban environment group.

3.4. Methodological Quality Assessment

Resulting from the risk of bias assessment, 17 RCT studies (18 cases) were conducted using RoB 2, and 4 NRCT studies were conducted using ROBINS-I.
In the evaluation of studies using RoB 2, 10 studies were at the risk of bias level of “some concerns”, and eight studies were classified as “high risk” (Figure 2a).
Regarding the randomized process, most studies proved that there was no problem with randomization through baseline analysis. In 11 studies, it was possible to hide the intervention and evaluation methods until the participant was assigned to an intervention, but in seven studies, this was not possible. Therefore, the inability to hide the method was evaluated as “high risk” in seven studies. In one study, it was possible to hide the intervention until it was assigned, but this study was judged to be of “some concerns” because it was difficult to determine the homogeneity between the groups owing to the small number of participants.
Regarding deviations from intended interventions, in most studies participants and study attendants were aware of the assigned interventions. In addition, one study in which dropouts occurred did not prove that they were irrelevant to the trial context. Therefore, the five studies that did not mention or consider dropouts were determined to be at the risk level of “some concerns”.
Regarding missing outcomes, one study was evaluated as “high risk” because no information was available regarding the missing outcomes data. However, most studies reported data from all, or almost all, participants and were evaluated as “low risk”.
Regarding the outcome measurements, 17 studies widely used metrics and provided evidence of these. The evaluator was aware of the intervention in most studies, but the possibility of this prior knowledge affecting the outcome was judged to be low. Therefore, one study with uncertain measurements was evaluated as “high risk”, whereas 17 studies were evaluated as “some concerns”.
Regarding the selection of results, 10 studies were reviewed by the ethics committee and these were evaluated as “low risk” because the pre-research protocol was appropriate and the results were reported clearly. Of the eight studies that did not mention protocols, seven were evaluated as “some concerns”, and one as “high risk” because it did not provide sufficient evidence of the analysis method selection.
In the evaluation using ROBINS-I, four studies were evaluated as “serious risk” (Figure 2b). Studies that were judged to have confounding factors in the pre-intervention stage were evaluated as “high risk”, and those with consistent controls were evaluated as “moderate risk”. In addition, the study with the same period of intervention was “low risk”, and the one with different time periods was “moderate risk”. In the intervention phase, all studies were evaluated as “low risk” because they clearly reported activities and locations. There were no missing data in the post-intervention stage, but this stage was evaluated as “high risk” because the participants knew of their intervention and evaluation methods conducted as a self-reporting questionnaire. In addition, studies judged to have prior protocols were evaluated as “low risk”.

4. Discussion

Recently, research on forestry and virtual reality (VR) interventions has been conducted in several countries. Previous systematic reviews have focused on the visual effects of indoor forests or the stress effect of forest appreciation through virtual reality [34,35]. However, a systematic review of the effect of a green environment through virtual reality on psychology has not yet been conducted. Therefore, this study systematically analyzed previous studies on the psychological changes in study participants when they experienced a green environment in virtual reality. Consequently, this review included and analyzed 21 studies and provides a discussion that could be helpful for future research using virtual reality and forests.

4.1. Emotional Restoration

Several studies reported a significant effect of experiencing virtual green environments on more than 50% of the emotional restoration indicators, and showed that emotional recovery had improved by more than 80%. This is consistent with the results of studies showing that experiencing a forest improves mood and emotions [63]. In addition, it was found that the effect on negative emotions was more significant than on positive emotions for all the characteristics of duration, observation position of the landscape, interaction, environment description, and sensory type. As a result, virtual natural contact tends to alleviate negative emotions more effectively than it elicits positive emotions. This finding is supported by previous studies which showed that it is more effective negative emotions than positive emotions [64,65]. Therefore, emotional recovery can be achieved, not only by real-life nature experiences but also by experiencing nature in a virtual environment [49].

4.2. Duration of Exposure to Nature

According to the results of the studies on the effect of duration, the ratio of all psychological results showed significant effects in the group that experienced nature for more than 10 min compared to the group that was exposed to nature for less than 10 min. In several studies, mood improved within 10 min of observing nature [66,67], but overall it was found to be mood improved more significantly when the experience continued for more than 10 min in this study. Regarding this result, we believe that experiencing a natural environment for longer periods of time will be psychologically more effective. However, it is essential to consider that if the equipment is used for a prolonged period, fatigue or dizziness can occur [68].

4.3. Observation Position of the Landscape

The classification according to the observation position of the landscape revealed that emotional recovery was achieved more effectively in the open-view environment that resembled a landscape, than in the in-forest environment. However, all observation positions were found to be significant for more than half of all participants. Therefore, the natural environment, regardless of observation position, is thought to be helpful for emotional recovery. According to Kaplan’s attention restoration theory (ART), exposure to nature has a psychological recovery effect by reducing mental fatigue [69,70]. However, a study conducted using an in-forest view showed a significant effect on cognitive recovery. This result supports that of Shin et al., who reported that cognitive function was significantly improved when walking in a forest, and therefore there is strong evidence that exposure to the natural environment is effective for cognitive recovery [71].

4.4. Methodological Quality Assessment

A methodological quality assessment was performed to evaluate bias in the final selection of the 21 studies. RoB 2 was used to evaluate RCT or randomized crossover study, and ROBINS-I was used to assess NRCT. As a result, the overall bias in 17 studies was rated as “some concern” or “high risk”. In RoB 2, most studies judged to be ”high risk” in the randomization process or selection of the reported result were evaluated overall as “high risk”. In ROBINS-I, studies judged to be at serious risk of bias due to confounding, deviations from intended interventions, or measurement of outcomes, were evaluated as “serious risk” overall.
Many studies on forest interventions are considered a risk or concern because of the intervention’s inherent characteristics rather than the disadvantages of the research design [38]. This is because the participants could not be unaware of the situation in which they saw, walked, experienced the forest, or participated in the study. Therefore, to ensure randomization and minimize bias due to confounding factors, it is necessary to secure a sufficient number of participants and conduct many studies to increase reliability [38]. To minimize concerns in the selection of the reported results and bias due to deviations from intended interventions, it is necessary to obtain approval from an accredited institution at the beginning of the study and report all accurate figures and interpretations of the derived results [72]. Psychological indicators are generally measured using self-reporting methods. Such methods may reduce the reliability of the research results and cause bias [73]. Therefore, to reduce the risk of bias in the outcome measurement, it is necessary to determine the suitability of participants in advance using high-reliability indicators. Additionally, physiological or biochemical indicators that can objectively measure changes may be used.

4.5. Direction of Future Studies

Research reported since 2020 accounted for approximately 80% of the 21 studies on the psychological effects of nature-based experienced using VR, and it can be seen that research on virtual reality has increased rapidly in recent years. Therefore, we believe that an increasing amount of research on virtual reality experiences will be conducted in the future owing to the development of technology. As most of the available research has been conducted recently, it is necessary to increase the reliability of the results by conducting continuous research in the future. Although most studies included in this review used virtual reality, augmented reality also has many advantages. Using augmented reality, participants can participate directly, improve achievement, and motivate learning [74]. Therefore, research on the effectiveness of forest education or forest experience activities using augmented reality is also needed in the future. In addition, although virtual nature experiences are unfamiliar to some educators, they can be a suitable medium for students to experience nature [54]. Therefore, more research is needed on the emotional, physiological, and physical effects of virtual forests on human well-being.
Virtual technology allows people to engage or participate, in a similar way to reality, with things that are difficult to see or experience, and it is accessible to people who have limited time or place restrictions [75]. However, access to virtual technology may be restricted by the time, development, and costs required at the initial stage [76]. Therefore, there is a need to provide opportunities to experience virtual technology at a national institution or a recreational forest and to develop a manual to facilitate the learning and use of the different types of virtual technology available. In addition, it is necessary to improve the evidence and quality of individual studies by presenting guidelines to researchers.
In this study, 29 interventions were categorized and analyzed from 21 studies, and indicators were classified into emotional recovery, cognitive recovery, stress reduction, and other indicators. Furthermore, according to the characteristics of the intervention, the duration, observation position of the landscape, interaction, environment description, and sensory type were categorized. However, it was impossible to derive results for a specific participant or the same intervention because the study design, such as participant, intervention, control, and test indicators, was subdivided. Nevertheless, this study is meaningful because it categorizes the intervention characteristics and analyzes the effects of virtual nature experiences on psychological indicators. In future studies, it is possible to perform meta-analysis through the accumulated results by implementing physiological and biochemical indicators that can be used together with psychological indicators. Therefore, many studies using forests and virtual technologies are needed for sustainable participation and development.

5. Conclusions

This review provides a narrative synthesis of the psychological effects of a green environment experience using virtual technology. A total of 21 studies, conducted in a green environment such as virtual forests, trees, and parks, were reviewed, and the majority of these studies reported positive psychological effects. However, it is difficult to generalize the results of the current systematic review; therefore, additional verification through continuous research is required in the future. Virtual reality is an intervention that anyone can experience in a short time, and forests experienced through virtual environments can be used to improve the psychological health of people. It can be especially helpful in situations where mental health problems are rapidly increasing worldwide owing to the health, economic, and social effects of the COVID-19 pandemic.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13101625/s1, Table S1: PRISMA 2020 checklist.

Author Contributions

Conceptualization, M.L., E.K., J.C. and G.K.; methodology, E.K. and G.K.; software, M.L. and E.K.; formal analysis, J.C. and S.C.; investigation, M.L., J.C. and S.C.; resources, S.C., S.H. and G.K.; data curation, S.C. and J.C.; writing—original draft preparation, M.L., J.C. and E.K.; writing—review and editing, S.C., S.H. and G.K.; visualization, M.L. and E.K.; supervision, G.K.; project administration, G.K. and S.H. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 13 01625 g001 550
Figure 1. Flow diagram illustrating the selection process.
Figure 1. Flow diagram illustrating the selection process.
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Figure 2. Risk of bias in included studies: (a) Risk of bias in randomized controlled trials using the RoB 2 tool; (b) Risk of bias in non-randomized controlled trials using the ROBINS-I tool.
Figure 2. Risk of bias in included studies: (a) Risk of bias in randomized controlled trials using the RoB 2 tool; (b) Risk of bias in non-randomized controlled trials using the ROBINS-I tool.
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Table
Table 1. Eligibility criteria for study selection.
Table 1. Eligibility criteria for study selection.
PICOS
Element		Inclusion CriteriaExclusion Criteria
PopulationStudies on the general population.Studies not including human participants.
InterventionStudies reporting any intervention that uses virtual technology (e.g., VR, AR, 360°, 3D) and the green environment.Studies not providing a description of the virtual technology and green environment where the intervention was held.
ComparatorStudies with a comparison group (e.g., exposure to real green environment, non-natural experience, other comparative intervention).Studies without comparable comparison group to virtual green space.
OutcomeAny quantitative psychological outcome.Studies not including quantitative psychological outcomes.
Study DesignRandomized controlled trials (RCTs), crossover study, non-randomized controlled trials (NRCTs), and pre–post test design.Review, case study, case–control study, cross-sectional study, and protocol study.
Table
Table 2. Search keywords.
Table 2. Search keywords.
KeywordsInclusion Criteria
PNA
I(“virtual reality” OR “virtual” OR “VR” OR “AR” OR “immersive experience” OR “augmented reality” OR “mixed reality” OR “simulation” OR “simulated” OR “CG” OR “3D” OR “virtual nature” OR “virtual forest” OR “virtual scenery” OR “virtual environment” OR “HMD” OR “virtual space” OR “immersive technology” OR “360”)
AND
(“forest” OR “landscape” OR “natural environment” OR “nature” OR “shinrin-yoku” OR “natural therapy” OR “nature walk” OR “green space” OR “park” OR “adventure” OR “nature connection” OR “plant” OR “nature connectedness” OR “wood”)
CNA
O(“psychological stress” OR “QoL” OR “POMS” OR “PANAS” OR “self-esteem” OR “STAI” OR “psychological” OR “self-efficacy” OR “psychological resilience” OR “well-being” OR “PRS” OR “CNS” OR “MSBS” OR “SPANE” OR “BDI” OR “BAI” OR “depression” OR “MRJPQ” OR “SSS” OR “ROS” OR “SSQ” OR “DASS” OR “self-reported” OR “mood” OR “psychologically” OR “relaxation” OR “stress reduction” OR “restoration”)
S(“RCT” OR “randomized controlled” OR “randomly” OR “intervention study” OR “pretest” OR “posttest” OR “crossover study” OR “pilot study” OR “randomized” OR “filed experiment” OR “field study” OR “comparative study” OR “empirical study” OR “field test” OR “crossover trial”)
Table
Table 3. Main characteristics of the included studies.
Table 3. Main characteristics of the included studies.
First Author
(Year)
[Ref]		CountryParticipantNFemale
(%)		Age
(M ± SD)		InterventionVirtual Technology (Equipment)TimeControl GroupOutcome MeasurementStudy DesignIRB
Emamjomeh
(2020) [42]		USAUniversity students3522.923.5 ± 3.2Explore the virtual space through restored office place with trees outside windowIVE (HMD; HTC vive-pro)5 min(n = 35) Real office place & trees outside window
(n = 35) 3D office place and no trees
(n = 35) real office place and no trees		PANAS (PA(+/), NA (*)); visual working memory(+/); IPQ(general(/), spatial presence(/), involvement(*), realness(/)Randomized crossoverX
Lähtevänoja
(2020) [43]		FIPrimary school students57NANA(n = 19) See the restored forest, sky, the flying butterfly with bird soundsVR (HMD; HTC Vive Pro-headset)5 min(n = 19) Free break
(n = 19) No break		ROS(*); Problem-solving ability(/)pre-posttest designX
Yu
(2018) [44]		TWHealthy adults3056.720 to 35See the restored natural forest and waterfall with the sound of cicadas, rivers, etc.VR (HMD; HTC vive VR)9 min 30 sec
Restored subway station and shopping plaza with traffic soundtrackPOMS(depression(*), tension(*), anger-hostility(*), fatigue(*), confusion(*), vigor(*), self-esteem(*))Randomized crossoverO
Yu
(2020) [45]		TWHealthy adults3482.458.8 ± 8.4See the restored trail in dense forest, waterfall, trees, river with natural soundsVR (HMD; Samsung Gear VR)10 minRestored cityPOMS(depression(*), tension(*), anger-hostility(+/), fatigue(*), confusion(*), vigor(+/), total(*)); RCS(Being away(*), Extent(*), Fascination(*), Compatibility(*)); SART(*)crossoverX
Gromala
(2015) [46]		CHAdults with chronic pain1322.949.0 ± 8.2(n = 7) See the restored mountains and trails with the sound of MBSRDeepstream VR (Firsthand Technology)12 min(n = 6) Listening only MBSRNRS(*)RCTX
Valtchanov
(2010) [47]		CAUniversity students2254.517 to 26(n = 12) Freely explored a forest setting
with natural sounds, air freshener, rumble pad shook		VR (HMD; nVIS, Reston, VA)10 min(n = 10) Watched a slideshow of abstract paintingsZIPERS(PA(*), negative(+/)); Math Quiz(/)RCTX
Mostajeran
(2021) [48]		GEAdult3432.427.3 ± 4.1360° videos were played mixed forest
with natural sounds		360° videos (HMD; HTC vive-pro)6 min(n = 34) Nature slideshows on the screen
(n = 34) City slideshows on the screen
(n = 34) City 360° videos		STADI-S(depression(/), anxiety(/)); POMS(Total(*), Fatigue(*)); SSSQ(/); PSS(/); IPQ(general(*), spatial presence(*), involvement(*), realness(*); SSQ(*)crossoverO
Reese
(2022) [49]		GEAdult5261.524.2 ± 3.7Virtual reality nature walk through a restored urban forest with bird soundsVR (HMD; OculusRift)7 minShort nature walk through adjacent forestPANAS(PA(*), NA(*)); SSS(+/); SVS(+/)RCTO
Kim
(2021) [50]		KRHealthy adult7450.039.0Virtual reality relaxation in real famous scenery with a relaxing soundtrackVR (HMD; Samsung Gear VR)10 min 30 sceBiofeedback relaxationSTAI-X1(*); NRS(*)Randomized crossoverO
Li
(2021) [51]		CHUniversity students with mild-to-moderate anxiety and depression18959.820.3 ± 2.6Restored environment including lawn, garden, water, forest
(1) (n = 35) Visual experience
(2) (n = 37) Interactive activities
(3) (n = 40) Interactive activitie: fishing
(4) (n = 38) Interactive activitie: watering		VR (HMD; HCT Vive Pro Eye sets, helmet, handles, 2.0 locators, locators brackets)10 min(n = 39) VR urban environment visual experience(1) PANAS(PA(/), NA(*)); GSES(*)
(2) PANAS(PA(*), NA(*)); GSES(+/)
(3) PANAS(PA(+/), NA(*)); GSES(*)
(4) PANAS(PA(/), NA(*)); GSES(+/)		RCTO
Jo
(2022) [52]		KRPeople with mild depression, stress, and anxiety6050.024.3 ± 2.4Forest experience with natural soundsVR (HMD; HTC- Vive pro, HD-650)3 minUrban or waterfront area experience VRPOMS(TA(*), DD(+/), AH(*), VA(*), FI(*), CB(*), FR(*), TMD(*))RCTO
Yin
(2020) [53]		USAHealthy adult10063.029.2 ± 11.8(1) (n = 25) Explore indoor green plants
(2) (n = 25) Explore outdoor green view through windows
(3) (n = 25) Combination both (1) and (2)		VR (HMD; HTC Vive VR headset)6 min(n = 25) Green-free office(1) STAI(+/)
(2) STAI(*)
(3) STAI(*)		RCTO
Sneed
(2021) [54]		USAUniversity students7360.325.7 ± 8.8Experience a virtual nature area
along a wooded trail and pond		360° videos (HMD)10 min(n = 25) Real-life nature
(n = 21) Virtual library		HNC(NRS(*), SINS(*))RCTO
Newman
(2022) [55]		UKAdult1650.043.0 ± 17.0(a) Graphical representation of the
restored experience including lake, tree and sky		VR (HMD; VIVE, in-ear headphones)10 minReal forest or video filmed from the real experiencePANAS-X(PA(/), NA(/), serenity(*))RCTX
12084.220.0 ± 2.5(b) Feel like a walk
(1) (n = 30) High realism natural
(2) (n = 30) Low realism natural		VR (HMD; VIVE, in-ear headphones)10 min(n = 30) High realism built
(n = 30) Low realism built		(1) PANAS-X(PA(*), NA(*), serenity(*))
(2) PANAS-X(PA(*), NA(*), serenity(*))		RCTO
Schebella
(2020) [56]		AUAdult5253.837.6 ± 10.6Spent time in real parks
(1) Low biodiversity with natural sounds (one bird, tree leaves) and natural single scent
(2) Moderate biodiversity with natural sounds (two birds, tree leaves) and two different natural scents
(3) High biodiversity with natural sounds (four birds, tree leaves) and three different natural scents
(4) High biodiversity only visual		IVE (HMD; Oculus Rift)5 minUrban with single scent(1) VAS(Stress(*), Anxiety(*), Calmness(+/), Insecurity(+/), Happiness(*))
(2) VAS(Stress(+/), Anxiety(+/), Calmness(+/), Insecurity(+/), Happiness(+/))
(3) VAS(Stress(+/), Anxiety(+/), Calmness(+/), Insecurity(+/), Happiness(+/))
(4) VAS(Stress(+/), Anxiety(+/), Calmness(+/), Insecurity(+/), Happiness(+/))		RCTX
Browning
(2020) [57]		USAHealthy university students9847.620.0 ± 1.2See the restored real forest with natural soundsVR (Samsung Gear VR headset)6 minReal forest setting in front of a blank white wallPANAS(PA(/), NA(*)); PRS(*)RCTO
Schutte
(2017) [58]		AUUniversity students2661.534.5 ± 12.6Experience natural virtual reality environments including eucalyptus trees, a meadow, and a stream
with natural sounds		360° videos (Samsung 360° virtual reality headset)6 minVR city environmentPANAS(PA(*), NA(+/))RCTO
Huang
(2020) [59]		CHHealthy university students8950.623.0 ± 2.8See the 3D courtyard with grass or a courtyard with treesVR (oculus headset)10 minCourtyard devoid of any vegetationPANAS(PA(*), NA(*))RCTX
Chan
(2021) [60]		SGYoung adults3070.020.5 ± 1.5Walking on the forest area while holding onto fixed handle bars with the sound of light windVR (HMD; HTC vive-pro)5 min3D downtown area with the sound of white noisePANAS(PA(+/), NA(*)); CNS(*)crossoverO
Seniors2090.072.7 ± 8.8Walking in the forest area while moving hands with the sound of light windVR (HMD; HTC vive-pro)3 min3D downtown area with the sound of white noisePositive(*), CNS(*), self-reported stress(+/)crossover
Nukarinen
(2020) [61]		FIUniversity students and staff2454.226.0Sitting quietly in a forest with the soundscape
(1) Rendered 3D
(2) VR 360° video shot in the physical location		VR 3D, 360° video(HMD; HTC vive headset)10 minSitting quietly in a forest in a real natural environment(1) PANAS(PA(/), NA(+/)); working memory(+/)
(2) PANAS(PA(/), NA(*)); working memory(+/)		RCTX
Wang
(2020) [62]		TWGeneralized anxiety disorder (age 50 to 75)7749.459.1(n = 40) Bike riding in a VE of natural scenery including forests, parks, trees and rivers3D (Cave VE system)20 min(n = 37) Bike in VE with abstract paintingsPerceived Stress(*); GDA(*)RCTO
M: Mean; SD: Standard deviation; CNS, Connectedness to Nature Scale; GAD, Generalized anxiety disorder 7–item; GSES, General Self-Efficacy Scale; IPQ, Igroup Presence Questionnaire; MBSR: Mindfulness-based stress reduction; NRS, Numerical Rating Scale; PANAS, positive and negative affect schedule; POMS, Profiles of Mood States; PRS, Perceived Restorativeness Scale; PSS, Perceived Stress Scale; RCS, Restorative Components Scale; ROS, restoration outcome scale; SART, Sustained Attention to Response Test; SINS, State of Independence with Nature Scale; SSQ, Simulator Sickness Questionnaire; SSS, standard stress scale; SSSQ, Short Stress State Questionnaire; STADI, State Trait Anxiety Depression Inventory; STAI, State Trait Anxiety Inventory; SVS, Subjective Vitality Scale; VAS, Visual Analogue Scales; ZIPERS, Zuckerman Inventory of Personal Reaction Scale; RCT: Randomized controlled trial; IRB: Institutional Review Board; *: significant effect; +/: nonsignificant effect on positive outcome; /: nonsignificant effect.
Table
Table 4. Outcomes according to the intervention type conducted in the included studies.
Table 4. Outcomes according to the intervention type conducted in the included studies.
Intervention DurationObservation PositionInteractionEnvironment DescriptionSensory Type
More than
10 min		Under 10 minIn-ForestOpen-ViewInteractionNon-InteractionRestoration EnvironmentReal EnvironmentVisual OnlyVisual and Other
%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m%p%p + m
Emotional Restoration67.682.453.193.955.688.970.090.063.695.557.486.965.785.754.291.772.084.053.491.4
   positive56.368.845.095.050.086.750.066.750.090.050.080.855.677.844.488.958.375.045.887.5
   negative77.894.458.693.160.690.978.6100.075.0100.062.991.476.594.160.093.384.692.358.894.1
Cognitive Restoration62.587.550.075.077.877.80.0100.00.050.070.090.020.060.085.7100.00.0100.063.681.8
Stress100.0100.012.575.022.277.8--33.3100.016.766.733.3100.016.766.7100.0100.012.575
Other Effect75.0100.075.075.085.7100.050.050.044.466.7100.0100.054.572.7100.0100.050.070.0100100
   IPQ--62.562.5100.0100.025.025.025.025.0100.0100.025.025.0100.0100.025.025.0100100
   Self-esteem--100.0100.0--100.0100.0--100.0100.0--100.0100.0--100100
   Self-efficacy50.0100.0--50.0100.0--33.3100.0100.0100.050.0100.0--50.0100.0--
   Numerical Rating100.0100.0100.0100.0100.0100.0100.0100.0--100.0100.0100.0100.0100.0100.0--100100
   Interaction nature100.0100.0100.0100.0100.0100.0--100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0100100
Including Study[45,46,47,50,51,54,55,59,61,62][42,43,44,48,49,52,53,56,57,58,60][43,45,46,47,48,49,51,52,54,55,56,57,60,62][42,44,50,53,58,59,61][42,47,49,51,53,58,60,62][43,44,45,46,48,50,51,52,54,55,56,57,59,61][42,43,46,47,49,51,53,55,59,60,61,62][44,45,48,50,52,54,56,57,58,61][42,51,53,54,55,59,62][43,44,45,46,47,48,49,50,52,56,57,58,60,61]
%p: ratio of significant effect; %p + m: ratio of both significant and non-significant effect on positive outcome.
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Lee, M.; Kim, E.; Choe, J.; Choi, S.; Ha, S.; Kim, G. Psychological Effects of Green Experiences in a Virtual Environment: A Systematic Review. Forests 2022, 13, 1625. https://doi.org/10.3390/f13101625

AMA Style

Lee M, Kim E, Choe J, Choi S, Ha S, Kim G. Psychological Effects of Green Experiences in a Virtual Environment: A Systematic Review. Forests. 2022; 13(10):1625. https://doi.org/10.3390/f13101625

Chicago/Turabian Style

Lee, Mijin, Eunsoo Kim, Jiwon Choe, Seonhye Choi, Siyeon Ha, and Geonwoo Kim. 2022. "Psychological Effects of Green Experiences in a Virtual Environment: A Systematic Review" Forests 13, no. 10: 1625. https://doi.org/10.3390/f13101625

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