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Article

Exposure to Familiar Virtual Nature Promotes Pro-Environmental Behavior: Experimentally Examining the Mediating Role of Nature Connectedness

by
Can Tao
,
Huiwen Xiao
,
Luxiao Wang
and
Ziqiang Xin
*
Department of Psychology, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(4), 1482; https://doi.org/10.3390/su17041482
Submission received: 13 January 2025 / Revised: 7 February 2025 / Accepted: 10 February 2025 / Published: 11 February 2025
(This article belongs to the Section Psychology of Sustainability and Sustainable Development)
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Abstract

:
Pro-environmental behavior (PEB) is crucial for achieving a sustainable future. Although prior research has investigated the relationship between virtual nature exposure and PEB, empirical findings have been inconsistent; some studies suggest a positive association, while others report null effects. Furthermore, the use of laboratory tasks to assess PEB often risks conflating it with cooperative behavior, potentially undermining the validity of the conclusions. To address these limitations, this study employed a double-randomization design, utilizing the Greater Good Game (GGG) as a measure of PEB. This research comprised two main studies, each consisting of two sub-studies. Study 1 examined the direct effect of virtual nature exposure on PEB (Study 1a) and the moderating role of familiarity with nature exposure (Study 1b). Study 2 included two phases: Study 2a investigated the effects of familiarity with nature exposure on both nature connectedness and PEB, while Study 2b implemented a randomized pre–post-intervention design to manipulate nature connectedness and examine its causal effect on PEB. Results indicated that virtual nature exposure more effectively enhanced PEB when participants were exposed to familiar virtual environments, and nature connectedness mediated this relationship. These findings provide insights into the reasons for previous inconsistencies and offer valuable practical implications for educational programs and policies aimed at promoting sustainable behaviors.

1. Introduction

Rapid urbanization and technological advancements have reduced human interactions with nature [1], leading to diminished environmental awareness and engagement in sustainable behaviors [2,3]. Consequently, virtual nature exposure (e.g., digital nature imagery, videos) has emerged as a potential solution to promote pro-environmental behavior (PEB) [4,5,6,7,8]. However, the effectiveness of this approach and its underlying mechanisms remain unclear [9], which limits the development of evidence-based interventions. Understanding these mechanisms is crucial for designing effective virtual nature experiences that can promote sustainable behaviors. This study investigates how virtual nature exposure influences PEB, with a focus on the role of familiarity and nature connectedness, aiming to bridge this gap and inform practical strategies for policymakers, educators, and urban planners.

1.1. Virtual Nature Exposure’s Impact on Health and PEB

Nature exposure, defined as human interaction with natural environments and non-human species, has been demonstrated to have benefits for physical and mental health [10,11], well-being [12], cognitive function [13], and reduced stress and anxiety [14], as well as to enhance pro-social behavior [15,16]. However, as opportunities for direct nature interaction diminish, virtual nature experiences have emerged as a cost-effective and accessible alternative. This shift has prompted researchers to explore the potential of virtual nature exposure in fostering pro-environmental activities [2,5,9,17,18,19,20].
Previous research has primarily focused on the positive effects of virtual nature exposure on physical and mental health, as well as cognitive function, often finding results comparable to those of real nature exposure [21]. However, research on the impact of virtual nature exposure on pro-environmental behavior (PEB) remain limited and have yielded inconsistent findings. Some studies have demonstrated a positive association [4,5,17]. For instance, Arendt and Matthes found that individuals increased their donations to environmental organizations after viewing nature documentaries compared to a control group [22]. However, others have reported null findings [9,23,24]. For example, Mayer et al. observed heightened concern after exposure to nature imagery, but this did not translate into corresponding increases in pro-environmental actions [8], and Klein et al. found no significant difference in PEB between exposure to nature and urban images [23].
This inconsistency may stem from a lack of systematic control and investigation of the characteristics of virtual natural environments (e.g., type, quality, presentation modality) or from variations in the measurement of PEB across studies. Therefore, this study aims to resolve these inconsistencies by examining the influence of familiarity with virtual nature exposure on PEB, employing the GGG as its measurement instrument.

1.2. Pro-Environmental Behavior: Definition and Measurement

PEB encompasses a variety of actions that individuals and groups undertake to protect and enhance the environment [25,26], including energy conservation, water management, waste recycling, pollution reduction, and biodiversity preservation [27]. By promoting ecosystem health and environmental quality through intentional actions in daily life and professional activities [28], PEB plays a vital role in achieving global sustainability goals. Given increasing environmental challenges, fostering widespread PEB is essential for creating a sustainable future.
PEB is commonly assessed through self-report measures, field observations, and laboratory observations [29], all of which have inherent limitations. Self-report measures are susceptible to self-serving biases [30,31]. Field observations, using methods such as informants, trained observers, or technical devices (e.g., GPS tracking) [32], offer greater ecological validity but are limited by higher data collection costs and the complexity of field settings, which can reduce experimental validity. Laboratory observations maximize experimental control, but this is at the cost of reduced ecological validity due to their artificial environment [29]. The virtual fishing game FISH is a well-established task used to assess PEB within a simulated common dilemma [33,34]. Participants act as fishers and make repeated decisions about how many fish to catch from a shared resource across multiple seasons. Each fish caught yields a small reward, but the fish population regenerates only if enough fish remain at the end of each season. This creates a conflict between maximizing individual short-term gains and ensuring the long-term sustainability of the fish population. While restraint in FISH can be interpreted as both PEB (prioritizing the resource) and cooperation (benefiting all players), these constructs are not always synonymous. As Klein et al. point out, cooperative actions can sometimes have negative environmental consequences [6,35]. Thus, it is necessary to differentiate between actions motivated by environmental concern and those driven by a desire for cooperation.
To differentiate PEB from cooperation, Klein et al. developed the Greater Good Game (GGG; see Figure 1), a nested public goods game played in anonymous groups of three [35]. In this game, participants can choose to carry out the following: (a) keep their endowment (selfish); (b) contribute to the public goods account (cooperative); or (c) contribute to the environment account (PEB). Contributions are doubled and either redistributed to the group or donated to an environmental organization, respectively. This design ensures that PEB and in-group cooperation are mutually exclusive and is analyzed using a two-stage multinomial processing tree (MPT) model, with the parameter s representing selfishness and the parameter e representing PEB [36,37]. The GGG has been shown to be a valid measure of PEB. Specifically, Klein et al. reported a significantly higher e parameter in the environmental priming condition [6].

1.3. The Effect of Familiarity with Virtual Nature Exposure on PEB: The Mediating Role of Nature Connectedness

Previous studies have consistently demonstrated a positive relationship between direct contact with nature and PEB [9,12,38,39,40]. However, as real-world interactions with nature decline [2], research has increasingly focused on the effects of virtual nature exposure on PEB [8,41]. While virtual nature exposure provides an alternative means of connecting with nature, its impact on PEB remains inconsistent [9,22,24]. This inconsistency suggests the influence of moderating variables. Specifically, this study investigates how familiarity with virtual nature exposure influences PEB through the mediating role of nature connectedness.
This proposal is grounded in self-expansion theory [42], which posits that individuals incorporate external elements into their self-conception, thereby fostering attachment and a sense of responsibility [43,44]. Familiarity with natural environments strengthens this self-expansion process by deepening personal identification with nature, making individuals more likely to integrate these environments into their self-conception. Research indicates that familiar environments are more likely to elicit positive emotions, enhance cognitive ease, and encourage sustained engagement. This leads individuals to pay greater attention to, feel more responsible for, and revisit such places [45,46,47]. When individuals perceive familiar natural environments as part of their self-conception, pro-environmental actions become a form of self-preservation, thereby increasing their likelihood of engaging in PEB [48,49]. Thus, familiarity may serve as a crucial factor that amplifies the effectiveness of virtual nature exposure in fostering sustainable behavior.
The integration of nature into the self is central to the concept of nature connectedness [50], which serves as the proposed mediator in this study. Nature connectedness encompasses the affective, cognitive, and behavioral dimensions of the human–nature relationship [28]. This study specifically focuses on the cognitive dimension, adopting Schultz’s definition of the Inclusion of Nature in the Self (INS) as a measure of nature connectedness [48]. The INS assesses the perceived interconnectedness between the self and nature, capturing the extent to which nature is integrated into an individual’s self-conception [48]. Empirical evidence consistently demonstrates a positive relationship between nature connectedness and various pro-environmental behaviors, including energy conservation, waste reduction, and participation in environmental activism [28,51,52].
Given the inconsistent findings in the existing literature regarding the impact of virtual nature exposure on PEB, this study first investigates this relationship. We propose the following competing hypotheses:
H1. 
Virtual nature exposure has a positive effect on PEB.
H2. 
Virtual nature exposure has no significant effect on PEB.
Subsequently, assuming that H1 is supported, this study further investigates the moderating role of familiarity and the mediating role of nature connectedness.
H3. 
Familiarity moderates the effect of virtual nature exposure on PEB such that familiar exposure has a stronger positive impact on PEB than unfamiliar exposure.
H4. 
Nature connectedness mediates the effect of familiarity with virtual nature exposure on PEB.

1.4. Research Gaps

Research on the relationship between nature contact and PEB has yielded valuable insights; however, several key limitations necessitate further investigation. First, existing studies often rely on measurement approaches that pose challenges to validity. To address these measurement concerns and improve the accuracy of PEB assessment, the present study employs the GGG paradigm developed by Klein et al., which utilizes quantitative model parameters to differentiate between in-group cooperative choices and genuinely pro-environmental choices [6,29].
Second, while direct experience with nature has consistently been shown to be associated with increased pro-environmental activities [9,12,38,39], virtual nature exposure yields inconsistent effects [8,24,41]. We propose that this inconsistency arises from a critical yet often overlooked moderator: environmental familiarity. Real-world nature experiences typically occur in familiar settings, while virtual environments encompass a wide range of settings, from highly familiar to entirely novel ones, which may influence subsequent PEB. To clarify the inconsistent findings in the literature concerning the relationship between virtual nature and PEB, this study explores the moderating role of environmental familiarity. This investigation is grounded in self-expansion theory [53], which posits that individuals are intrinsically motivated to incorporate external entities into their self-conception. We propose that familiar natural environments are more readily integrated into the “self”, fostering a stronger ecological self and, consequently, promoting PEB.
Third, previous investigations of nature connectedness as a mediator in the relationship between nature contact and PEB have often relied on cross-sectional, correlational designs [4,17,52], which preclude strong causal inferences [54]. Consistent with the recommendations of Spencer et al. [55], who advocate for prioritizing experimental designs to establish causal chains, the present study employs a double-randomization design to investigate the mediating role of nature connectedness [55,56,57]. Unlike cross-sectional approaches, this design establishes temporal precedence by measuring variables at two distinct time points and incorporating conceptual replication with diversified measurement strategies, thereby enhancing the validity of causal claims and strengthening both internal and external validity [57,58].
This study addresses three limitations in the existing literature: (1) the reliance on potentially biased traditional PEB measures; (2) the lack of clarity regarding the moderating role of environmental familiarity in the relationship between virtual nature exposure and PEB; and (3) the inability of prior research to establish causal inferences regarding the mediating role of nature connectedness.
In conclusion, this research offers potential contributions to environmental psychology and sustainability practice. Theoretically, our findings may extend self-expansion theory by proposing virtual environmental familiarity as a novel antecedent of nature internalization processes while suggesting nature connectedness as a potential mediator between virtual nature exposure and pro-environmental behavior. Methodologically, the double-randomization design provides preliminary causal evidence that addresses limitations observed in prior cross-sectional studies, though further validation is needed. Practically, the results could inform the design of interventions aimed at promoting sustainable behaviors.

1.5. The Current Study

This research comprised two main studies, each consisting of two sub-studies. Study 1 aimed to examine the effect of virtual nature exposure on PEB and the moderating role of environmental familiarity. Specifically, Study 1a investigated the influence of exposure to virtual nature (vs. urban images) on PEB, while Study 1b examined the effects of familiar (vs. unfamiliar virtual nature) on PEB. Study 2 employed a double-randomization design to experimentally investigate the mediating role of nature connectedness in the relationship between familiar virtual nature exposure and PEB. Study 2a manipulated familiarity with virtual nature and explored its influence on nature connectedness and PEB. Study 2b further manipulated nature connectedness using a pre–post-intervention design to examine its causal effect on PEB.

2. Study 1: Virtual Nature Exposure and PEB

2.1. Study 1a: The Impact of Virtual Nature Exposure on PEB

2.1.1. Design

Study 1a employed a between-subjects design to examine the effect of virtual image exposure (nature vs. urban) on PEB. Participants were randomly assigned to view either nature or urban images. PEB, the dependent variable, was measured using the parameter e from the GGG. Demographic variables, including gender, age, education level, and residence, were also considered in the analysis.

2.1.2. Participants

An a priori power analysis was conducted using multiTree software (v0.47) [59], based on the results from Klein et al. [35]. Assuming a medium effect size (parameter s = 0.20), a power (1 − β) of 0.80, and an alpha level (α) of 0.05, the analysis indicated that a sample of 626 observations was required to detect a difference in the parameter e between the urban condition (e = 0.10) and the nature condition (e = 0.21). With five game rounds per participant, this yielded a minimum required sample of 125 participants. This study recruited 140 participants. Two participants were excluded from the analysis due to missing data. Following the exclusion of data, the final sample for Study 1a comprised 138 participants (690 observations across the five rounds). The participants’ mean age was 30.30 years (SD = 8.29). The sample consisted of 97 female participants (70.29%), 102 participants (73.91%) who possessed a bachelor’s degree or higher, and 129 participants (93.48%) residing in urban areas. All participants provided informed consent prior to participation, and the study was approved by the Institutional Review Board of Department of Psychology at Renmin University of China.

2.1.3. Experimental Materials

Pro-environmental behavior. PEB was assessed using the GGG [35], a multi-round, multi-player game designed to evaluate PEB within a social context. Participants were randomly assigned to anonymous groups of three and, in each round, received an initial endowment. Participants allocated funds across three accounts: a private account, a public goods account, and an environment account. Funds allocated to the public goods account were doubled and then distributed equally among group members, representing a pro-social, in-group benefit. Funds allocated to the environment account were also doubled and donated to the China Environmental Protection Foundation [59], representing a direct contribution to environmental sustainability. Funds allocated to the private account were retained by the individual. This design created trade-offs between individual and collective benefits, as well as between pro-social (in-group) and pro-environmental benefits [6].
Figure 2 illustrates the multinomial processing tree (MPT) models used to analyze the decision processes [35]. These models decompose the decision process into distinct cognitive processes, each associated with a probability parameter. Specifically, the parameter s represents the probability of engaging in selfish behavior (i.e., maximizing personal gain regardless of the consequences for others), thereby distinguishing selfish from non-selfish choices (probability 1 − s). In the case of non-selfish choices, the parameter e represents the probability of exhibiting PEB (i.e., contributing to the environmental account), distinguishing PEB (probability e) from in-group cooperation (i.e., contributing to the group account; probability 1 − e).
Image Familiarity Rating. Participants rated the familiarity of each image using a 5-point Likert scale (1 = very unfamiliar; 5 = very familiar), which was displayed below the image in the center of the screen.
Image Materials. Sixteen color photographs (eight depicting urban environments and eight depicting natural environments) were selected based on criteria from Nisbet et al. [51]. The photographs were chosen to represent typical urban and natural scenes. To ensure that familiarity with the images would not confound the results, a preliminary analysis was conducted. This analysis confirmed that there was no significant difference in image familiarity between the urban and natural image sets.

2.1.4. Procedure

The experiment was conducted online using Credamo, a platform designed for online research. Prior to participation, all participants provided informed consent and completed a brief demographic questionnaire. The participants were then randomly assigned to one of two conditions: the nature condition (n = 64) or the urban condition (n = 74). In the nature condition, participants viewed eight landscape photographs (e.g., forests, mountains, lakes) for 5 s each. In the urban conditions, participants viewed eight photographs depicting urban scenes unrelated to nature (e.g., cityscapes, buildings, streets), also for 5 s each.
Following the image presentation, participants received detailed instructions and illustrative examples of the GGG. These instructions included a clear explanation of the game’s objective, the different account types (private, public goods, and environment), and the consequences of allocation decisions. In each of the five rounds, the initial endowment (CNY 1–3, in CNY 0.50 increments) was randomly ordered for each participant. The participants received feedback only at the end of the experiment.
To establish a context of social impact, the participants were informed that the accumulated funds would be donated to the China Environmental Protection Foundation, a leading environmental organization in China [59]. Each participant received a base payment of CNY 5. To incentivize consistent performance across all five rounds, one of the five rounds of each participant’s earnings (from both their public and private accounts) was randomly selected by the computer for an additional bonus payment. The participants were not informed of this study’s purpose until after the experiment was completed.

2.1.5. Data Analysis

Parameters were estimated using MultiTree software, a statistical tool specifically designed for MPT analysis [59]. MultiTree employs maximum-likelihood estimation to fit models and generate parameter estimates within a defined MPT structure. The model fit was evaluated using goodness-of-fit indices, including the likelihood ratio statistic (G2) and the Akaike Information Criterion (AIC). To test for significant differences in the parameter e between groups, various constrained models were compared to a baseline model. The baseline model allowed all parameters to be freely estimated without any equality constraints. In contrast, the constrained model imposed equality constraints on specific parameters. For example, to test for a significant difference in e between the treatment group and the control group, a constrained model restricting etreament = econtrol was constructed. Model comparisons were conducted using likelihood ratio tests, evaluating differences in G2 and the AIC. A better fit for the baseline model compared to the constrained model indicated that the imposed equality constraint was untenable, suggesting a significant difference in the parameter e between the two groups.
Study 1a compared nature and urban conditions using an MPT model with distinct parameter settings for each condition (see Figure 2 for tree diagrams and parameters: snature, enature, surban, and eurban). To test H1: (enature > eurban), we tested against the null hypothesis of no difference (enature = eurban). Rejecting the null hypothesis would support H1; failing to reject it would be consistent with H2.

2.1.6. Results and Discussion

Table 1 presents the choice proportions and parameter estimates for s and e in the GGG across all conditions. The results show a greater PEB in the nature group. The observed proportion of pro-environmental choices in the nature condition (0.42) was higher than that in the urban condition (0.23). Furthermore, the parameter e was higher in the nature group (enature= 0.53; SE = 0.031) compared to the urban group (eurban = 0.37; SE = 0.032). Imposing the constraint enature = eurban resulted in a significant reduction in model fit compared to the baseline model (ΔG2 = 13.14; p < 0.01; ΔAIC = 1490.96), indicating a significant difference in PEB between the nature and urban groups. Additionally, the parameter s was lower in the nature group (snature = 0.21; SE = 0.023) than in the urban group (surban = 0.38; SE = 0.025), which is consistent with prior research demonstrating that contact with natural environments promotes pro-social behavior [16,60].
In summary, Study 1a utilized a between-subjects design to examine the effect of viewing nature versus urban images on pro-environmental behavior (PEB). Consistent with prior research [5], the results demonstrated a significant positive effect of nature exposure on PEB, supporting H1.
This effect can be explained through several interacting mechanisms. First, attention restoration theory suggests that virtual nature replenishes attentional resources, thereby reducing mental fatigue and freeing cognitive capacity for pro-environmental actions [61,62]. Second, the biophilia hypothesis posits that humans have an innate connection to nature [63], which can be activated through exposure to virtual nature, fostering a sense of connectedness and promoting PEB [64,65]. Third, the positive emotions elicited by virtual nature, such as awe and tranquility, may broaden thought–action repertoires [66], encouraging altruistic and pro-environmental behaviors [18,67]. These emotions may also enhance the sense of connection to nature, further promoting PEB [68].
While the connection between nature and PEB is well established, the influence of specific environmental characteristics, such as familiarity, remains underexplored. Study 1b addressed this gap by examining how familiarity moderated the relationship between virtual nature and PEB.

2.2. Study 1b: The Moderating Role of Familiarity

2.2.1. Design

Study 1b employed a between-subjects design to examine the effect of familiarity (familiar vs. unfamiliar) on PEB. Participants were randomly assigned to view either familiar or unfamiliar natural images. PEB, the dependent variable, was assessed using the parameter e from the GGG. Gender, age, residence (city/rural), and education level were included as covariates.

2.2.2. Participants

As described in Study 1a, the necessary sample size was 626 observations, ensuring sufficient power to detect the hypothesized effects. With five game rounds per participant, this yielded a minimum required sample of 125 participants. A total of 130 participants were recruited. After excluding participants who did not respond attentively, the final sample for Study 1b consisted of 128 participants (each completing five GGG trials, yielding 640 observations). The participants’ mean age was 30.92 years (SD = 8.21), with 93 females (73.44%), 80 held a bachelor’s degree (62.50%), 26 held a graduate degree (20.31%), and 122 resided in urban areas (96.09%). All participants provided informed consent prior to participation, and the study was approved by the Institutional Review Board of the Department of Psychology at Renmin University of China.

2.2.3. Experimental Materials

Image Materials. Sixteen color photographs of natural landscapes were used in this study. Eight images depicted familiar Chinese scenery, including well-known Chinese landmarks such as Mount Huangshan. The remaining eight images depicted exotic scenery unfamiliar to most Chinese participants, including scenes from the Amazon rainforest and Antarctic icebergs. Participants rated the familiarity of each image using a 5-point Likert scale (1 = not at all familiar; 5 = very familiar). Welch’s t-test revealed that the mean familiarity rating for the familiar images (M = 3.54; SD = 0.58) was significantly higher than that for the unfamiliar images (M = 2.85; SD = 0.86; t(115) = 5.29; p < 0.001).

2.2.4. Procedure

The experiment was conducted online using the Credamo platform. Prior to participation, all participants provided informed consent and demographic information. The participants were randomly assigned to one of two conditions: the familiar nature image condition (n = 66) or the unfamiliar nature image condition (n = 62). Participants in the familiar nature condition viewed photographs of natural landscapes with Chinese characteristics, while those in the unfamiliar nature condition viewed photographs of natural landscapes from foreign countries. Each participant viewed eight images presented in a randomized order for 5 s each. Following each image presentation, participants rated their familiarity on a 5-point Likert scale. Finally, all participants completed the GGG using the same procedure as in Study 1a.

2.2.5. Data Analysis

The data analysis procedures mirrored those employed in Study 1a.

2.2.6. Results and Discussion

Table 2 presents the choice proportions and parameter estimates for s and e in the GGG across all conditions in Study 1b. The results indicated that the parameter e was higher in the familiar nature condition (efamiliar = 0.58; SE = 0.031) compared to the unfamiliar nature condition (eunfamiliar = 0.45; SE = 0.032). Comparing the constrained model (efamiliar = eunfamiliar) with the baseline model revealed a significantly better fit for the baseline model (ΔG2 = 7.53; p = 0.006; ΔAIC = 5.53). These results indicate that PEB was significantly higher in the familiar nature group than in the unfamiliar nature group.
In summary, familiar natural settings promoted PEB more effectively than unfamiliar settings, supporting H3. This finding may help explain the inconsistent results observed in prior studies regarding the effect of virtual nature exposure on PEB, as these studies may have overlooked the influence of familiarity with virtual nature contact. To further examine the underlying mechanism of this effect, Study 2 employed two experiments to investigate the mediating role of nature connectedness in the relationship between virtual nature exposure and PEB.

3. Study 2: Experimentally Testing the Mediating Role of Nature Connectedness

To examine the mediating role of nature connectedness in the relationship between virtual nature exposure and PEB, this study employed experimental designs that manipulated both the independent variable (X) and the mediator (M). This approach strengthened causal inferences and enhances internal validity by reducing the influence of confounding variables [54,55,57].

3.1. Study 2a: The Effect of Virtual Nature Exposure on Nature Connectedness and PEB

3.1.1. Design

Study 2a examined the effects of the independent variable on both the dependent and mediating variables, using a between-subjects design (familiar nature group, unfamiliar nature group). The dependent variable was the individual-level, pro-environmental parameter ei, calculated as the proportion of pro-environmental choices made by each individual out of the total number of non-selfish choices. Nature connectedness was examined as a mediating variable. Gender and age were included as control variables.

3.1.2. Participants

An a priori power analysis using G*Power 3.1 indicated that a minimum sample size of 102 participants was required to achieve a power of 0.80 (1 − β) at an alpha level (α) of 0.05, assuming a medium effect size (Cohen’s d = 0.5). A total of 140 participants completed the study. After excluding eight participants due to inattentive responses, the final sample comprised 132 participants (mean age = 29.31 years; SD = 8.58). The sample consisted of 87 females (65.91%) and 45 males (34.09%); 99 held a bachelor’s degree (75.00%) and 23 held a master’s degree (17.42%); and 121 participants resided in city areas (91.67%). All participants provided informed consent prior to their participation.

3.1.3. Experimental Materials

The Inclusion of Nature in the Self (INS) Scale. The INS, adapted from Aron et al.’s relationship closeness measure, assesses the degree to which individuals include nature in their self-conception [53]. This single-item measure presents seven pairs of overlapping circles representing “self” and “nature”, as illustrated in Figure 3, with greater overlap visually indicating a stronger perceived connection. This scale has been widely used and has demonstrated good reliability and validity [8].
The experiment used the same sixteen images (eight familiar Chinese landscapes and eight exotic landscapes) as study 1b.

3.1.4. Procedure

Participants were randomly assigned to either the familiar (n = 66) or unfamiliar nature (n = 66) condition. They viewed eight images, each presented for 5 s, and subsequently rated the familiarity of each image on a 5-point Likert scale. Following the familiarity ratings, participants completed the INS scale to assess their nature connectedness [48]. Finally, participants completed 10 rounds of the GGG, as described in Study 1b; initial endowments ranged from 0.5 to 5 points, in increments of 0.5.

3.1.5. Data Analysis

Double-randomization designs employ two distinct experimental phases to establish causal mediation. Initially, the independent variable (X) is manipulated, and both the proposed mediator (M) and the dependent variable (Y) are assessed to determine the effects of X on M and X on Y. Subsequently, in a separate experiment with an independent sample, the mediator (M) is directly manipulated, and the dependent variable (Y) is measured to isolate the M–Y relationship. This two-stage process allows for stronger causal inferences regarding the mediating role of M than that which can be achieved through traditional correlational or single-manipulation designs.
To investigate the mediating role of nature connectedness (M) in the relationship between familiarity with nature exposure (X) and PEB (Y), two linear regression models were constructed.
Model 1 examined the effect of familiarity with nature exposure (X) on nature connectedness (M). In this model, ins represented the connectedness to nature score; familiarity was a binary variable (0 = unfamiliar nature group; 1 = familiar nature group); gender was a binary variable (0 = female; 1 = male); and age was a continuous variable.
ins = β0 + β1 · familairity + β2 · gender + β3 · age + ε
Model 2 examined the total effect of familiarity with nature exposure (X) on PEB (Y). The individual-level parameter ei, representing each participant’s PEB level, served as the dependent variable. The independence and control variables were the same as in Model 1.
ei = β0 + β1 · familairity + β2 · gender + β3 · age + ε
Preliminary tests showed no significant differences between groups in potential control variables (gender, age, education level, and residential location), suggesting that the group assignment was random and that the influence of these control variables could be considered negligible.
Prior research indicates that gender, age, education level, and residential location may impact nature connectedness and PEB [69,70,71,72] and including them in the model could improve estimation accuracy [73]. We therefore explored models with different combinations of these variables. When all control variables were included, education level (bachelor’s degree) exhibited high multicollinearity (VIF = 5.6). We found that models including only gender and age as control variables yielded the highest R-squared values (Model 1: R2 = 0.1612; F(3, 128) = 8.20; p < 0.001; Model 2: R2 = 0.0726; F(3, 128) = 3.34; p < 0.05) and demonstrated good overall fit. Including education level and residential location resulted in non-significant F-statistics in Model 2 (F(8, 123) = 1.69; p = 0.1067). Therefore, we retained only gender and age as control variables in both models to ensure robust results.

3.1.6. Results and Discussion

Prior to the main analyses, group differences in the control variables were assessed. Chi-square tests of independence indicated no significant differences between the familiar and unfamiliar nature groups in gender (χ2(1) = 0.03; p = 0.85) or residential status (χ2(1) = 2.48; p = 0.12). Independent-sample t-tests revealed no significant differences in age (t(130) = −0.96; p = 0.34) or education level (t(130) = −1.45; p = 0.15), suggesting that the assignment to the two groups was random.
The regression results are presented in Table 3. Model 1, with connectedness to nature as the dependent variable, revealed a statistically significant effect of familiarity with nature exposure on nature connectedness (F(3, 128) = 8.20; p < 0.001), explaining 16% of the variance in nature connectedness (R2 = 0.16). The coefficient for familiarity with nature exposure (familiar nature group = 1; unfamiliar nature group = 0) was 0.90 (t (128) = 4.58; p < 0.001), indicating that the familiar nature group reported significantly higher levels of nature connectedness than the unfamiliar nature group.
Model 2, with PEB as the dependent variable, showed a significant effect of familiarity with nature exposure on PEB (F(3, 128) =3. 34; p = 0.02). The model explained 7.3% of the variance in PEB (R2 = 0.073). The coefficient for familiarity was 0.11 (t (128) = 2.54; p = 0.022), indicating that the familiar nature group had a higher PEB than the unfamiliar nature group.
This study examined the effect of familiarity with natural environments on individuals’ nature connectedness and PEB. The results indicated that the familiar nature group reported significantly higher nature connectedness than the unfamiliar nature group, again supporting H3. To further investigate the mediating role of nature connectedness, Study 2b used experimental manipulation to test the causal relationship between nature connectedness and PEB.

3.2. Study 2b: The Effect of Nature Connectedness on PEB

3.2.1. Design

To investigate the causal influence of nature connectedness on PEB, Study 2b employed a within-subjects design. Participants completed a pre-test one week prior to the experimental manipulation of nature connectedness. This design allowed for the examination of the causal impact of the manipulated variable on subsequent PEB.

3.2.2. Participants

A power analysis using G*Power 3.1 indicated that to detect a medium effect size (Cohen’s d = 0.5) with a significance level of α = 0.05 and a power of 0.80, a minimum sample size of 34 participants was required. To account for potential attrition, 39 participants were initially recruited online. Of these, 34 undergraduate students aged 21 to 30 years (M = 23.03 years; SD = 1.85 years) completed both the pre-test and post-test and were included in the final analysis. The final sample comprised 25 females and 9 males. All participants provided informed consent before participating in the experiment.

3.2.3. Experimental Materials

The Inclusion of Nature in the Self (INS) scale and the GGG used to assess PEB in Study 2a were also employed in this study.

3.2.4. Procedure

One week prior to the experimental intervention, participants completed a pre-test session, during which they provided informed consent, and completed a demographic questionnaire, measures of connectedness to nature, and the GGG (as described in Study 2a). One week following the pre-test, participants completed a post-test session. This session involved a 10 min free walk in a designated natural area on campus, during which participants were instructed to document three aspects of natural beauty that captured their attention using their mobile phones. Upon completion of the walk, participants submitted these recordings to the researcher via a designated online platform. This procedure was designed to enhance participants’ connectedness to nature through the direct experience and documentation of natural elements [74]. Subsequently, participants’ connectedness to nature and the GGG (as described in Study 2a) were reassessed.

3.2.5. Analysis

To verify the effectiveness of the nature walk and documentation intervention in enhancing connectedness to nature, a manipulation check was conducted. Paired-sample t-tests were performed to compare participants’ connectedness to nature scores for the pre-test and post-test. Then, paired-sample t-tests were used to compare the participants’ scores on ei between the pre-test and post-test.

3.2.6. Results and Discussion

Table 4 presents the descriptive statistics for connectedness to nature before and after the intervention. The results indicate a statistically significant increase in connectedness to nature scores from the pre-test (M = 4.44; SD = 1.46) to the post-test (M = 5.26; SD = 1.46; t(33) = −2.31; p = 0.027; d = 0.56). These findings suggest that the intervention effectively enhanced individuals’ connectedness to nature, providing preliminary support for the intervention’s effectiveness.
Paired-sample t-tests also revealed a statistically significant increase in the parameter e from the pre-intervention (M = 0.33; SD = 0.30) to the post-intervention (M = 0.63; SD = 0.33; t (33) = 4.38; p < 0.001; d = 0.95). These findings indicate that the intervention promoted PEB.
Overall, Study 2 provided strong support for the hypothesis that nature connectedness mediates the relationship between familiar nature exposure and PEB, supporting H4. The findings replicate and extend previous research [74], demonstrating that walking while documenting pictures in nature activity effectively enhances nature connectedness and promotes pro-environmental behaviors. These interventions hold promise for real-world applications, such as integrating them into environmental education programs to enhance awareness of nature, incorporating green spaces into urban design to strengthen nature connectedness, and informing policymaking to encourage sustainable behaviors.

4. Discussion

4.1. The Influence of Familiarity with Virtual Nature Exposure on PEB

This study examined the influence of familiar and unfamiliar virtual natural environments on PEB and its underlying mechanisms, with a focus on implications for promoting sustainable practices. The findings revealed that familiar virtual natural environments, compared to unfamiliar ones, significantly enhanced PEB through the mediating role of nature connectedness. These findings contribute to the literature on virtual nature contact and PEB within environmental psychology, offering practical insights for designing effective virtual interventions to promote public engagement in sustainable actions. Specifically, this research highlights the importance of environmental familiarity in designing impactful virtual nature experiences that strengthen individuals’ nature connectedness and, consequently, foster increased PEB, contributing to broader sustainability goals.
Study 1, comprising two sub-studies, explored the influence of virtual nature contact on PEB. Study 1a demonstrated that exposure to virtual natural environments can enhance PEB, consistent with some previous findings [38,39,40,75]. However, other studies have reported null results [8,9,23], suggesting that specific characteristics of virtual nature contact may be influential. Study 1b revealed that familiar virtual nature promotes PEB more effectively than unfamiliar virtual nature, potentially explaining these inconsistencies. This study proposes the familiarity of the virtual natural environment as a key moderator.
Beyond examining direct effects, this study also investigated the mediating mechanisms through which virtual nature contact influences PEB. Building on prior research demonstrating positive relationships between nature contact and nature connectedness and between nature connectedness and PEB [40,51], Study 2, consisting of two sub-experiments, focused on the mediating role of nature connectedness. Study 2a provided initial support for the effect of familiar virtual nature exposure on PEB via nature connectedness. Study 2b, which employed the experimental manipulation of nature connectedness, provided strong confirmation of its mediating role, thereby contributing to a deeper understanding of the psychological processes involved.
These findings suggest that familiar virtual nature contact enhances the ecological self, thereby promoting PEB. According to self-expansion theory [76], individuals expand their self-conception by connecting with the environment. Experiencing familiar virtual nature facilitates this connection, incorporating nature into self-conception. This self-expansion motivates PEB [49]. This aligns with research on connectedness to nature, which suggests that stronger connectedness promotes a shift towards broader social and environmental concerns [4,40,41].

4.2. Implications

This study presents three main contributions. First, it expands the scope of research on the antecedents of PEB and provides a novel perspective for explaining inconsistencies in previous findings regarding the relationship between nature contact and such behavior. Prior research has predominantly focused on the differential effects of natural versus urban contact on PEB, emphasizing comparisons between urban and natural settings [7,12,24,26]. This approach has neglected variations within natural environments, specifically the impact of varying degrees of familiarity with these environments on pro-environmental actions. This study innovatively introduces the concept of “familiarity with virtual natural environments” and demonstrates that contact with familiar natural environments has a more pronounced effect on PEB than contact with unfamiliar ones. This finding not only enriches the literature on the antecedents of PEB but also offers a potential explanation for previous inconsistencies: these discrepancies may arise from overlooking or failing to adequately control familiarity with virtual natural environments.
Second, this study employed more effective measurement methods for PEB and mediation analysis. Employing a state-of-the-art paradigm for the measurement of PEB enhanced validity compared to measures of pro-environmental intentions and allowed for a more precise differentiation between pro-social and pro-environmental actions [35]. Furthermore, the mediating role of nature connectedness was examined through a double-randomization design [54,57]. Prior research utilizing traditional regression to examine the mediating role of nature connectedness has been criticized for its limitations in establishing causal relationships [77]. The present study addressed this limitation by employing an experimental approach, thereby providing more robust support for the mediating influence of nature connectedness.
Third, our findings offer practical implications for promoting public engagement in pro-environmental activities. The results demonstrate that familiarity with natural scenes plays a crucial role in influencing PEB, suggesting that familiar scenes may be more effective in environmental campaigns and educational settings. This highlights the importance of cultural relevance in environmental communication. Therefore, policymakers and organizations should carefully consider the cultural background and lived experiences of their target audiences when developing environmental communication materials and educational programs. Selecting natural scenes relevant to their living environment or cultural backgrounds should enhance the effectiveness of these initiatives. For instance, using marine-related scenes may be more effective for coastal residents than inland forest scenes. Similarly, for many individuals, images of frequently visited local parks or green spaces may be more effective in promoting PEB than images of distant rainforests.

4.3. Limitations and Future Research Directions

While this study supports the proposed hypotheses and offers theoretical and practical contributions, some limitations should be acknowledged. First, the use of the GGG in a laboratory setting to measure PEB, while superior to traditional self-report methods in capturing behavioral choices and differentiating between pro-social and pro-environmental actions, has limited ecological validity. This paradigm simulates resource allocation scenarios rather than real-world natural environments, and the influence of social desirability bias cannot be eliminated [31]. Future research could conduct field experiments to investigate PEB in more ecologically valid contexts. Furthermore, while our findings demonstrate the value of fostering nature connectedness to promote PEB, we acknowledge the limitations of individual-focused approaches. An overreliance on psychological interventions targeting individual PEB may risk neglecting the structural reforms that are crucial for systemic change. Although virtual nature experiences may influence general pro-environmental activities, it is essential to investigate whether these translate into tangible conservation actions. Future research should explore the extent to which such experiences lead to real-world behaviors, such as reduced consumption, increased recycling, or participation in environmental advocacy. Future research could utilize longitudinal designs with objective measures of real-world environmental behavior after virtual nature exposure.
Second, the present study focused primarily on the dimension of familiarity with virtual natural environments, neglecting other potentially influential variables. While our research explored general natural and green spaces (e.g., forests, mountains), the existing literature highlights the importance of environment type. For example, blue spaces (e.g., rivers, lakes, coastlines) have also been shown to promote PEB [78], including specific actions like reducing disposable plastic use [79]. Furthermore, the frequency of nature exposure is a crucial factor [80]. A study by Alock et al. found that a 1 SD increase in nature visits correlated with a 17% SD increase in general environmental behavior [81]. Temporal and spatial proximity to natural environments also plays a role. Research indicates that the availability of urban green space significantly impacts individuals’ perceived connection with nature, which, in turn, influences PEB [72]. These factors may independently influence PEB or interact with familiarity. Finally, emotional engagement warrants consideration. It is plausible that emotional responses (e.g., awe, tranquility) to familiar environments influence the relationship between familiarity and PEB, as individuals may feel a stronger sense of connection and likeness to places they know [18,67]. Future studies should explore the complex interplay of environment type, frequency, proximity, emotional engagement, and familiarity in shaping PEB.
Third, this study focused on virtual nature exposure and did not include a direct comparison with real nature experiences. While virtual nature offers a potentially valuable and accessible tool for promoting PEB, especially for those with limited access to natural environments, further research is needed to determine its effectiveness compared to real-world nature exposure. Additionally, the level of immersion in the virtual environment, along with the presentation modality (e.g., images, videos, VR) [6,7,82,83] and the spatiotemporal proximity of the environment to participants, may moderate the effects of familiarity. Future research should explore these interactions to provide a more nuanced understanding of the role of familiarity in influencing PEB.
Fourth, we acknowledge that the potential mechanisms underlying this relationship remain partially unexplored. Our focus on nature connectedness as a mediator aligns with the theoretical framework of self-expansion, yet alternative pathways—such as emotional arousal (e.g., positive affect) and cognitive restoration processes—were not empirically tested here due to scope constraints. Future research could systematically compare these mechanisms through multi-mediation models.

5. Conclusions

This study concludes that (1) virtual natural exposure can enhance PEB; (2) exposure to familiar virtual natural scenes promotes PEB more effectively than exposure to unfamiliar virtual natural environments; and (3) nature connectedness mediates the relationship between familiar virtual nature exposure and PEB.

Author Contributions

Conceptualization, C.T. and Z.X.; methodology, C.T.; software, C.T.; validation, C.T., H.X., and L.W.; formal analysis, C.T.; investigation, C.T.; resources, Z.X.; data curation, C.T.; writing—original draft preparation, C.T.; writing—review and editing, Z.X., H.X., and L.W.; visualization, C.T.; supervision, Z.X., H.X., and L.W.; project administration, Z.X.; funding acquisition, Z.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Major Project of the National Social Science Fund of China, No. 24&ZD158.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the Department of Psychology at Renmin University of China.

Informed Consent Statement

Informed consent was obtained from the participants to publish this paper.

Data Availability Statement

Data are not available due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 17 01482 g001
Figure 1. Illustration of Greater Good Game: participant choices and outcomes.
Figure 1. Illustration of Greater Good Game: participant choices and outcomes.
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Figure 2. A graphical representation of the baseline multinomial processing tree model for one condition (see Klein et al. [35]).
Figure 2. A graphical representation of the baseline multinomial processing tree model for one condition (see Klein et al. [35]).
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Figure 3. The Inclusion of Nature in the Self scale.
Figure 3. The Inclusion of Nature in the Self scale.
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Table 1. Number of participants, proportion of behavioral choices in GGG, and parameter estimates across two conditions.
Table 1. Number of participants, proportion of behavioral choices in GGG, and parameter estimates across two conditions.
Proportion of Behavioral ChoicesParameter Estimates
ConditionnSelfishCooperationPEBs (SE)e (SE)
Nature640.210.370.420.21 (0.023)0.53 (0.031)
Urban740.380.390.230.38 (0.025)0.37 (0.032)
Note. Parameter estimates are based on the raw choice frequencies of all participants over all trials; for instance, 64 (participants) × 5 (trials) =320 observations in the control condition.
Table 2. Number of participants, proportion of behavioral choices in Greater Good Game, and parameter estimates (standard error in parentheses) across two conditions.
Table 2. Number of participants, proportion of behavioral choices in Greater Good Game, and parameter estimates (standard error in parentheses) across two conditions.
Proportion of Behavioral ChoicesParameter Estimates
ConditionnSelfishCooperationPEBs (SE)e (SE)
Unfamiliar Nature660.290.380.320.29 (0.025)0.45 (0.032)
Familiar Nature620.190.340.470.19 (0.022)0.58 (0.0031)
Note. Parameter estimates are based on the raw choice frequencies of all participants over all trials; for instance, 66 (participants) × 5 (trials) =390 observations in the control condition.
Table 3. Effects of group on mediator and dependent variable.
Table 3. Effects of group on mediator and dependent variable.
Independent VariableDependent Variable
Model 1: Nature ConnectednessModel 2: e
βtβt
familiarity (unfamiliar = 0; familiar = 1)0.904.58 ***0.112.54 *
gender (female = 0; male = 1)0.371.77−0.038−0.80
age0.00120.100.00381.42
intercept4.411.72 ***0.465.30 ***
R20.16 0.073
N132 132
F8.20 *** 3.34 *
Note: * p < 0.05; *** p < 0.001.
Table 4. Results of paired-sample t-tests for pre- and post-test measures.
Table 4. Results of paired-sample t-tests for pre- and post-test measures.
VariablePre-TestPost-Testt
(n = 34)(n = 34)
MeanSDMeanSDDifferencet
Nature Connectedness4.441.465.261.46−0.82−2.31 *
e0.330.30.630.33−0.30−4.38 ***
* p < 0.05; *** p < 0.001.
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Tao, C.; Xiao, H.; Wang, L.; Xin, Z. Exposure to Familiar Virtual Nature Promotes Pro-Environmental Behavior: Experimentally Examining the Mediating Role of Nature Connectedness. Sustainability 2025, 17, 1482. https://doi.org/10.3390/su17041482

AMA Style

Tao C, Xiao H, Wang L, Xin Z. Exposure to Familiar Virtual Nature Promotes Pro-Environmental Behavior: Experimentally Examining the Mediating Role of Nature Connectedness. Sustainability. 2025; 17(4):1482. https://doi.org/10.3390/su17041482

Chicago/Turabian Style

Tao, Can, Huiwen Xiao, Luxiao Wang, and Ziqiang Xin. 2025. "Exposure to Familiar Virtual Nature Promotes Pro-Environmental Behavior: Experimentally Examining the Mediating Role of Nature Connectedness" Sustainability 17, no. 4: 1482. https://doi.org/10.3390/su17041482

APA Style

Tao, C., Xiao, H., Wang, L., & Xin, Z. (2025). Exposure to Familiar Virtual Nature Promotes Pro-Environmental Behavior: Experimentally Examining the Mediating Role of Nature Connectedness. Sustainability, 17(4), 1482. https://doi.org/10.3390/su17041482

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