# Benefits of a group-based running session on feelings of energy and fatigue: No augmenting effect of green exercise during the defoliation season

Fabien Legrand, Philippe Jeandet, Guillaume Polidori, Fabien Beaumont, Ryan Rhodes

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Fabien Legrand, Philippe Jeandet, Guillaume Polidori, Fabien Beaumont, Ryan Rhodes. Benefits of a group-based running session on feelings of energy and fatigue: No augmenting effect of green exercise during the defoliation season. Psychology of Sport and Exercise, 2025, 27, pp.102760. 10.1016/j.psychsport.2024.102760. hal-04729684

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# Benefits of a group-based running session on feelings of energy and fatigue: No augmenting effect of green exercise during the defoliation season

Fabien D. Legrand<sup>a,*</sup>, Philippe Jeandet<sup>b</sup>, Guillaume Polidori<sup>c</sup>, Fabien Beaumont<sup>c</sup>, Ryan E. Rhodes<sup>d</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

### Keywords:

- Aerobic exercise

- Feelings of energy and fatigue

- Affect

- Environment

- Forest volatile organic compounds (FVOCs)

## ABSTRACT

This randomized controlled trial investigated the impact of a brief session of group-based running on feelings of energy and fatigue, comparing exercise in a local nature reserve versus an outdoor built environment, and a sedentary control condition. Sixty-six physically active university students participated, with 56 providing full data for each time point. Consistent with previous research, participants in both exercise groups reported significantly increased energy and decreased fatigue compared to those in the sedentary control group. However, the type of outdoor environment did not significantly influence the magnitude of improvements. Contrary to expectations, there was no significant difference in energy enhancement or fatigue mitigation between participants who jogged in a local nature reserve versus those who jogged on a cinder track in an urbanized area. The study discusses potential reasons for this, including seasonal variations in forest volatile organic compounds (FVOCs) concentrations, which may impact the psychological effects associated with forest environments. Further research is needed to better understand the complex relationship between exercise, environment, and feelings of energy/feelings of fatigue.

In October 2020, the World Health Organization (WHO) acknowledged the existence of individual pandemic fatigue and issued a report formulating ways for governments to reinvigorate the public who were facing numerous constraints. Focusing on both feelings of fatigue and energy, a recent survey involving 1000 adults aged 18+ in the UK has unveiled worrying results among young adults, with many functioning at just over half (53%) of their usual energy/vitality levels (ProPlus®, 2023). This widespread fatigue is impacting the overall well-being of a third of adults (31%), plus 37% have taken time off work due to feeling tired despite not being ill. Around 80 percent of participants reported symptoms that were negatively affecting their well-being and daily lives, including low motivation (34%), headaches (26%), and poor concentration (25%). These symptoms are having a significant impact on quality of life, with a third of adults (31%) reporting a decline in their overall well-being, and one in five (22%) saying that their home life has been affected.

According to O'Connor and Puetz (2005), feelings of energy can be defined as pleasant feelings increasing one's capacity to complete

mental or physical activities. Conversely, feelings of fatigue relate to unpleasant feelings which define a reduced capacity to complete mental or physical activities. Feelings of energy and feelings of fatigue are complex experiences that can be influenced by various factors (Thayer, 2001) including medical conditions (chronic illnesses, infections, hormonal imbalances, and certain medications can induce fatigue), stress (engagement in enjoyed activities and a sense of purpose usually correlate with increased energy levels whereas persistent stress or anxiety can drain mental and physical energy, leading to fatigue), and circadian rhythms (feelings of energy and fatigue fluctuate throughout the day due to the body's internal clock).

Over the past two decades, research has indicated that a single bout of exercise training is among the most reliable ways to temporarily increase feelings of energy. A meta-analysis including 16 experiments that measured feelings of energy and feelings of fatigue tested a total of 678 participants (Loy et al., 2013). It revealed that a single bout of exercise increased energy compared to controls in 91% of the effect sizes calculated, and the standardized mean effect was 0.47. Exercise-induced

<footnote><sup>a</sup> Université de Reims Champagne-Ardenne, C2S, Reims, France</footnote>

<footnote><sup>b</sup> Université de Reims Champagne-Ardenne, INRAE, RIBP, USC1488, Reims, France</footnote>

<footnote><sup>c</sup> Université de Reims Champagne-Ardenne, ITHEMM, Reims, France</footnote>

<footnote><sup>d</sup> University of Victoria, Victoria, British Columbia, Canada</footnote>

<footnote>* Correspondence concerning this article should be Université de Reims Champagne-Ardenne, C2S, 51096, Reims, Cedex, France.
E-mail address: fabien.legrand@univ-reims.fr (F.D. Legrand).</footnote>
reductions in fatigue were less consistent. However, these experiments predominantly tested college students who completed moderate-intensity stationary cycling or strength training (i.e., indoor workouts) of 20–40 min duration. Exploring the revitalizing effects of exercise bouts of shorter duration is crucial since it reflects the real-world scenarios of many people who may not have the time or inclination for extended workouts. Indeed, negative feelings such as low energy typically encourage self-regulation strategies which can relieve negative affect in the very short term (Wagner and Heatherton, 2014, p. 616). As Thayer (2001) hypothesized, negative feelings create a sense of urgency which can encourage one to prioritize easy-to-use measures that only take a few minutes to get relief, such as junk food and salty snacks.

Research investigating green exercise (i.e., exercise undertaken in natural environments) has found that exercising in nature might confer benefits beyond those provided by physical activity in non-natural environments (Araujo et al., 2019). For instance, some studies have indicated that, compared against exercise in non-natural outdoors environments, green exercise can result in greater reductions in physiological and psychological stress, as well as greater mood improvements (e.g., Todorova et al., 2023). Several mechanisms might be responsible for these more positive mood effects associated with green exercise. First, green exercise might contribute to the satisfaction of the need for nature relatedness which, according to Baxter and Pelletier (2019), has to be viewed as one of the basic human psychological needs. A fundamental tenet of the Self Determination Theory (SDT; Ryan and Deci, 2017) is that a direct relationship exists between basic psychological needs satisfaction and psychological well-being (an illustration in the domain of sports/physical activity can be found in Quested and Duda, 2010). Another hypothesis is that natural environments may alter an individual's experience of exercise. A 2013 review found that participants' perceived exertion was lower in natural settings despite achieving a faster self-selected jogging speed (Gladwell et al., 2013). This reduction in perceived exertion has the potential to increase feelings of energy since some studies have found an inverse relationship between perception of physical exertion and self-reported vitality (e.g., Chandler-Laney et al., 2010). One last potential reason for the superiority of green exercise over exercise in non-natural environments relates to the inhalation of forest volatile organic compounds (FVOCs) emitted in the air by a variety of plants and trees. More than 500 types of FVOCs have been discovered to date (Antonelli et al., 2020), some of which (e.g., monoterpenoids) having been reported to increase alertness and vitality (Kennedy et al., 2011). Since engaging in effortful physical exercises such as brisk walking or running usually increases ventilation from resting values of around 10 L of air per minute (10 l/m) to > 100 l/m (McArdle et al., 2023), some authors have highlighted that exercise can intensify the magnitude of beneficial effects gained through the action of FVOCs (e.g. Lee and Maheswaran, 2011).

At present, there is a paucity of research testing the impact of short-duration green exercise bouts of less than 20 min on feelings of energy and/or feelings of fatigue. Based on the recent meta-analyses by Li et al. (2022) and Wicks et al. (2022), as well as on an extensive literature search by browsing PsycInfo, PubMed, and SPORTDiscus databases, we are aware of only 7 published studies that used a sound experimental method (i.e., including randomization or counterbalanced order of conditions, pre-tests and post-tests, and at least one non-exercise control group or condition) to compare the effects of short-duration (≤20 min) exercise in natural versus non-natural environments on feelings of energy and/or feelings of fatigue: Plante et al. (2007), Ryan et al. (2010), Rogerson et al. (2016), Kinnafick and Thogersen-Ntoumani (2014), Stigsdotter et al. (2017), Legrand et al. (2018), and Li et al. (2020). Findings are unclear at this stage with two trials (i.e., 29%) reporting statistically higher increases in energy/vitality or higher decreases in fatigue following green exercise (Ryan et al., 2010; Stigsdotter et al., 2017), while the other ones failed to replicate this result. Reasons for inconsistent findings might be attributable to a number of methodological issues including inadequate statistical power (three of the seven

studies had sample sizes ≤30: Rogerson et al., 2016, Kinnafick and Thogersen-Ntoumani, 2014, Legrand et al., 2018) and lack of control of exercise intensity (three of the seven studies did not measure exercise intensity: Ryan et al., 2010; Stigsdotter et al., 2017; Li et al., 2020). The lack of experimental control for participants' level of exertion is a significant issue given the well-established influence of this exercise parameter on affective responses to exercise (Ekkekakis et al., 2011). More specifically, an inverse relationship has been reported between exercise intensity and psychological well-being in the literature review by Ekkekakis et al. (2011), with positive affective changes occurring during and following exercise of both light and moderate intensities, but not for high or very high intensity exercise.

Hence, the main purpose of this randomized controlled trial was to examine the effects of a 14 min long bout of moderate-intensity green exercise (group-based running in a local nature reserve) on energy and fatigue mood states (feelings of energy and feelings of fatigue) in comparison to an identical exercise bout in a non-natural outdoor environment. In order to do so, we examined changes in participants' self-rated feelings of energy and fatigue occurring from before to after 14 min of group-based running performed in a nature reserve largely covered with trees and ground vegetation versus an outdoor built environment (cinder track) with only sparse vegetation nearby. A second aim was to compare changes in feelings of energy and fatigue in each of these two groups to a sedentary control group. This control group also involved a group-based (but sedentary) activity of similar duration, which ensured that potential changes in feelings of energy or feelings of fatigue in the exercise groups were not primarily determined by the effects of social interactions. Based on the meta-analyses by Wicks et al. (2022) and Loy et al. (2013) outlined earlier, it was expected that (1) changes in feelings of energy and feelings of fatigue would be more pronounced among participants who exercised in the nature reserve, and that (2) participants in the two exercise groups (but not those in the sedentary control group) would report increased feelings of energy.

# 1. Method

## 1.1. Study design and ethics

We employed a randomized controlled design with 3 different groups: jogging in a local nature reserve (J-LNR), jogging on a cinder track in an outdoor built environment (J-OBE), or watching a Youtube video on how physical activity can help improve cognitive function and brain health (sedentary control, CTRL). There were two independent variables (IV) in this study; namely study group (between-subject IV: J-LNR, J-OBE, and CTRL) and moment of assessment (within-subject IV: pre-intervention, post-intervention). Therefore, this randomized controlled trial was a 3/groups) x 2(moments of assessment) factorial study, with repeated measures on the last factor. The dependent variables (DVs) were feelings of energy (POMS-V) and feelings of fatigue (POMS-F). The study complied with the CONSORT reporting standards. The protocol for the present study has undergone ethical approval by the French national ethics committee (IRB00012476-2022-02-05-180) where details concerning study's aims, objectives, hypothesis, inclusion/exclusion criteria, sample size, and statistical analyses plans were provided. Data collection ran from the end of October 2023 to the end of November 2023.

## 1.2. Power calculation

Results of Wicks et al. (2022)'s meta-analyses comparing changes in feelings of energy and feelings of fatigue following outdoor physical activity in natural versus non-natural environments revealed effects sizes of *d* = 3.28 and *d* = -1.98 respectively (Wicks et al., 2022, p. 1054). In addition, the meta-analysis by Loy et al. (2013) indicated that in comparison to non-exercise control conditions, a single bout of aerobic exercise can enhance feelings of energy by an effect size of about 0.50 (Δ =
0.47). Given the smallest effect size of interest for the present study (0.47), the *a priori* power analysis for the within-between interaction of an ANOVA with three independent groups and two measurement periods (pre-test and post-test) with the settings of *f* = 0.25 (moderate effect size), *α* = .05 (*p*-value) and 1-β = 0.90 (power) yielded a required total sample size of 54 participants (G\*POWER, Faul et al., 2007). More participants than required were recruited to ensure sufficient statistical power because it was anticipated that a number of participants would cancel appointments due to transportation issues (there was no transport support for travel to appointments at the different study sites in the present research).

## 1.3. Participants

Sixty-six students from a medium-sized university in Northeastern France (42 males and 24 females), between the ages of 18 and 22 years (*M*<sub>age</sub> = 20.7, *SD* = 0.9), were recruited as unpaid volunteers using flyers posted at local teaching auditoriums and students' living quarters. Eligibility criteria included: a) being aged 18 or over, and b) being in possession of a valid medical certificate stating no contraindication to physical exertion to ensure that it was safe to perform the aerobic exercise bout. All participants were physically active, engaging in some form of physical activity at least three times a week due to their curriculum (sports sciences). Using a computer generated list of random numbers (Microsoft Excel; Microsoft, Redmond, WA), we randomized participants to one of the three following groups: aerobic exercise in a local nature reserve (J-LNR), aerobic exercise in an outdoor built environment (J-OBE), sedentary control group (Youtube video: CTRL). The random assignment to study groups was accomplished using a 1:1:1 ratio and was stratified according to participants' gender. Participants signed an informed consent before taking part in the study.

## 1.4. Measures

Energy and fatigue were measured using the vigor (V) and fatigue (F) subscales of the French version of the Profile of Mood States (POMS; McNair et al., 1992; Cayrou et al., 2003). The POMS provides six subscales: 1) anger, 2) confusion, 3) depression, 4) fatigue, 5) tension, and 6) vigor. Administration procedures require the respondents to read a list of 65 words (e.g., "friendly," "tense," "helpless") or short phrases (e. g., "unable to concentrate", "uncertain about things") that describe feelings that people have, and then indicate on a five-point Likert-type scale whether they experience each feeling or state. Each item is scored on a 5-point Likert-type scale (0 = not at all, 1 = a little, 2 = moderately, 3 = quite a bit, 4 = extremely). With the exception of vigor, higher scores indicate more adverse outcome on the subscale. Item examples for the fatigue and vigor subscales include "exhausted", "worn-out", and "energetic", "full-of-pep" respectively. Evidence indicates that POMS vigor and fatigue scores measure the intensity of energy and fatigue mood states (O'Connor, 2004). The use of the POMS vigor and fatigue subscales is recommended for measuring the intensity of energy and fatigue moods in short-term experimental settings (O'Connor, 2004). Only the fatigue and vigor scales of the POMS (referred to here as POMS-F and POMS-V) were selected for inclusion in the current study.

## 1.5. Procedure

In the J-LNR and J-OBE groups, participants were asked to jog at a slow pace for 14 min. If jogging was too hard, it could be alternated with brisk walking. The only requirement was to maintain heart rate within the range 55%-70 % of the age-predicted maximum heart rate (MHR), which is indicative of moderate intensity exercise according to the American College of Sports Medicine (Pollock et al., 1998). In line with the American College of Sports Medicine (ACSM) recommendations, age-predicted maximal HR (MHR) was estimated using the following equation: $MHR = 206.9-0.67 \times age$ (ACSM, 2010). Heart rate was

self-monitored continuously via a chest strap heart rate monitor and watch receiver (Polar RS400, Kempele, Finland). Such a device has been shown to have good criterion-related validity and is usually considered to be well-suited for recording heart rate during physical activity or exercise training (Engstrom et al., 2012).

In the J-LNR group, physical exercise took place in a local reserve known as the Montagne-de-Reims Regional Nature Park, a 500 sq. km vegetation and wildlife reserve in the Reims Mountains, on the sandstone massif between Epernay and Reims, northeastern France. This park is a plateau with more than 200 km of waymarked hiking trails. It is 90 percent covered with leafy trees including oaks (58 %), beeches (24 %), and chestnut trees (10 %). For participants in this group, a meeting point was set at the Route Forestière des Pins (forest road) 51380 Verzy, France (49.1352° N; 4.1514° E). Each meeting lasted 1 h and was organized for subgroups of 3-6 participants. In total, five sessions were held, which all took place between 2 p.m. and 4 p.m. on weekdays between October 26 and November 29, 2023. Participants came with their own vehicle. One of the authors (F.D.L.) was waiting for them on site. Upon arrival, the heart rate monitor (chest strap + watch) was installed; then the POMS-V and POMS-F subscales (paper-and-pencil version) were completed. Next, participants were instructed to run along the forest road at a slow pace for 7 min, then turn around to return to the starting point at the same pace. Participants were instructed to keep their heart rate within the prescribed range (55%-70 % MHR), with permission to run together and chat. Upon arrival, each participant filled out the POMS-V and POMS-F scales again. Finally, the heart rate monitors were collected, and participants' average heart rate value for the entire session was reported on the back of their last completed questionnaire. Weather was similar during all sessions and quite normal for the fall season in Northeastern France; that is around 6°C-9°C, with no precipitation but predominantly cloudy and breezy conditions.

In the J-OBE group, the exercise session was done on a 400 m cinder track located in a metropolitan urbanized area. This urbanized area consists of residential developments, nonresidential buildings, and light industry. The meeting point was at the SUAPS car park, chemin des rouliers 51100 Reims, France (49.1435° N; 4.0405° E), just above the cinder track. Each meeting lasted 1 h and was organized for subgroups of 3-6 participants. In total, five sessions were held, which all took place between 2 p.m. and 4 p.m. on weekdays between October 26 and November 29, 2023. Participants came with their own vehicle and one of the authors (F.D.L.) waited for them at the car park. The procedures and instructions were exactly the same as previously described for the J-LNR group. After fitting the heart rate monitor (chest strap + watch) and completing the POMS-F and POMS-V scales (paper-and-pencil version), participants went down to the track and were instructed to run at a slow pace for 14 min keeping their heart rate within the prescribed range (55%-70 % MHR), with permission to run together and chat. At the end of the session, they returned to the car park where the POMS-F and POMS-V scales were completed again. Then the heart rate monitors were removed, and the average heart rate value was recorded for each participant on the back of the last completed questionnaire. Weather was similar during all sessions and quite normal for the fall season in Northeastern France; that is around 6°C-9°C, with no precipitation but predominantly cloudy and breezy conditions.

In the sedentary control group (CTRL), participants had to watch a 14-min educational video about physical activity and its effects on brain health, a major topic taught to undergraduates at our sports sciences department (https://www.youtube.com/watch?v=QIvN9_QFaCs). This video was played on a television monitor (screen size: 165.1 cm, display resolution: 3840 x 2160 pixels) in a 25-square-meter room at our sports sciences department. Each meeting lasted 1 h and was organized for subgroups of 3-6 participants. In total, five sessions were held, which all took place between 2 p.m. and 4 p.m. on weekdays between October 26 and November 29, 2023. Participants came with their own vehicle. One of the authors (F.D.L.) was waiting for them on site. Upon arrival, the participants entered the room and completed the POMS-F and POMS-V
scales (paper-and-pencil version). Then they were asked to watch the video. They were allowed to chat with one another and were explicitly told not to fall asleep while watching. At the end of the video, they filled out the POMS-F and POMS-V scales again. For this group of participants, no monitoring or heart rate recording was carried out since the experimental task implied no physical effort to be performed at a pre-defined intensity. The video content was pre-screened for emotionally charged images or topics.

## 1.6. Data analysis

All statistical analyses were performed using the JASP software package (version 0.18.1; JASP team, 2023). Preliminary analyses were performed to check for data normality (Shapiro-Wilk's and Levene's tests). Potential outliers were detected for the difference between the post-intervention score (score 2) and the pre-intervention score (score 1) in feelings of energy and feelings of fatigue. This was done by calculating a z-value for each participant; $z = [(score 2-score 1)-M_{score 2-score 1}] \div [SD_{score 2-score 1}]$, with $z > 3.28$ identifying outliers with a probability of 0.001. In all analyses reported below, descriptive statistics are reported as means and standard deviations.

The first step of our statistical analyses focused on between-group differences in feelings of energy and feelings of fatigue at baseline. These were tested using two separate 1-way analyses of variance (ANOVAs). Then, the magnitude of pre-to post-intervention changes in energy and fatigue scores was compared between the three study groups using two separate 3 × 2 mixed-ANOVAs (three groups x two assessment points). For all analyses, p-values of ≤ 0.05 were considered statistically significant. In case of significant group × time interaction, follow-up independent samples t-tests using a Bonferroni-corrected p-value of 0.017 (0.05/3) were conducted. Finally, one independent sample t-test was employed to examine possible differences in heart rate while jogging in the two exercise groups (J-LNR and J-OBE) with statistical significance set at $p \le .05$.

Partial eta squared ($\eta_p^2$) was used to measure effect size estimates from all ANOVAs and were interpreted as representing the following magnitudes: 0.01 (small), 0.06 (medium), and 0.14 (large), Cohen (1988). To qualitatively interpret the magnitude of change in energy and fatigue score between pairs of groups, Cohen's *ds* and associated 95 % confidence intervals (95 % CI) were calculated. Cohen's *d* effect size values can be classified as small (0.2–0.5), moderate (0.5–0.8), and large (>0.8), Cohen (1988).

# 2. Results

## 2.1. Study population

Participants' baseline sociodemographic characteristics as well as self-reported levels of energy and fatigue are shown in Table 1. As can be seen, there was no between-group difference with respect to baseline (i. e., pre-intervention) scores in feelings of energy ($M_{J-LNR} = 14.1, SD = 7.5, M_{J-OBE} = 14.7, SD = 5.5, M_{CTRL} = 14.5, SD = 6.0, p = .952$) or feelings of fatigue ($M_{J-LNR} = 8.5, SD = 6.6, M_{J-OBE} = 9.1, SD = 7.5, M_{CTRL} = 9.4, SD = 7.5, p = .905$).

## 2.2. Preliminary analyses

Five participants in the J-LNR and five participants in the CTRL group did not complete the post-intervention self-report questionnaires within the first 5 min following the end of the exercise (or Youtube video) session. More specifically, all participants from one of the sub-groups composing the J-LNR group ($n = 5$) did not immediately complete the questionnaires right after their 14-min running session because they faced a heavy downpour at the very end of their run. Consequently, they quickly went to take shelter in their vehicles before they could be given the POMS-V and POMS-F questionnaires. Unfortunately, more

<caption>**Table 1**</caption>

Baseline characteristics of participants with baseline scores of fatigue and energy mood states by study group.

<table><thead><tr><th></th><th>CTRL (n = 22)</th><th>J-OBE (n = 22)</th><th>J-LNR (n = 22)</th><th>p-value (test)</th></tr></thead><tbody><tr><td>Age (SD)</td><td>20.9 (0.8)</td><td>20.9 (0.9)</td><td>20.4 (0.8)</td><td>.069 (1-way ANOVA)</td></tr><tr><td>Gender: M/F</td><td>14/8</td><td>15/7</td><td>13/9</td><td>.822 (chi-square)</td></tr><tr><td>Born in France</td><td>22</td><td>22</td><td>22</td><td>1.000 (chi-square)</td></tr><tr><td>French as 1st language</td><td>22</td><td>22</td><td>22</td><td>1.000 (chi-square)</td></tr><tr><td>Ethnicity</td><td></td><td></td><td></td><td>.621 (chi-square)</td></tr><tr><td>Caucasian</td><td>20</td><td>20</td><td>19</td><td></td></tr><tr><td>Maghrebi</td><td>1</td><td>1</td><td>3</td><td></td></tr><tr><td>Asian</td><td>1</td><td>1</td><td>0</td><td></td></tr><tr><td>POMS-F score (SD)</td><td>9.41 (7.49)</td><td>9.09 (7.45)</td><td>8.46 (6.62)</td><td>.905 (1-way ANOVA)</td></tr><tr><td>POMS-V score (SD)</td><td>14.50 (6.04)</td><td>14.68 (5.54)</td><td>14.09 (7.46)</td><td>.952 (1-way ANOVA)</td></tr></tbody></table>

Note. SD: standard deviation; M/F: males/females; CTRL: control group; J-OBE: jogging in an outdoor built environment (cinder track); J-LNR: jogging in a local nature reserve.

than 5 min elapsed before the downpour ended. In addition, all participants from one of the subgroups composing the CTRL group ($n = 5$) were forced to leave the room in which the Youtube video was projected because an evacuation drill (with fire alarm) was conducted. The order to evacuate was given a few seconds after the video ended, before the questionnaires could be distributed to the participants. Unfortunately again, more than 5 min elapsed before they were allowed to re-enter the room. As highlighted by Ekkekakis et al. (2019), the nature and amplitude of exercise-induced mood changes have been shown to be dependent on the timing of mood measurement following exercise. Consequently, these ten participants with missing data were discarded from statistical analyses (i.e., complete-case analysis). As a result, our study had a final number of 56 analyzed sets of questionnaires ($n_{J-LNR} = 17, n_{J-OBE} = 22, n_{CTRL} = 17$). Fig. 1 shows the flow of participants through each study stage. A complete-case analysis rather an intent-to-treat (ITT) analysis was adopted because no participants dropped out or withdrew in the present study. As Heymans and Twisk (2022) emphasized, a complete-case analysis can be valid when missing data are MCAR (missing completely at random). Data are said to be MCAR when causes of the missing data are unrelated to relevant study variables or outcomes (Heymans and Twisk, 2022), which is what happened in the present study.

Our preliminary statistical analyses revealed that there were no outliers for changes in feelings of energy or feelings of fatigue in any of the three study groups, and that exercise intensity did not differ between the two exercise groups ($M_{J-LNR} = 134$ bpm, $SD = 10; M_{J-OBE} = 128$ bpm, $SD = 17, p = .207$). These values correspond respectively to 69.3 % and 66.7 % of age-predicted MHR and are within the prescribed range of HR values (55%–70 % of age-predicted MHR).

Finally, no participant from either group discontinued before the prescribed duration, and only two participants from the exercise groups reported mean HR outside (below) the prescribed range. Therefore, a total of 54 participants (i.e., 96 %) complied with the study protocol.

## 2.3. Effects of implemented interventions on feelings of energy and feelings of fatigue

### 2.3.1. Energy

The mean levels of feelings of energy for each study group immediately before and after intervention are presented in Table 2. The mixed ANOVA on feelings of energy produced a significant group × time interaction, $F(2, 53) = 6.42, p = .003, \eta_p^2 = .19$. Follow-up t-tests
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Flowchart of study participants through the experiment. J-LNR = jogging in a local nature reserve, J-OBE = jogging on a cinder track in an outdoor built environment, CTRL = control sedentary group.</figcaption></figure>

indicated that in comparison to controls, participants in the J-LNR showed statistically significant pre-to post-intervention increases in feelings of energy; mean difference = 6.76 (95 % CI interval: 1.81 to 11.71, *p* = .009). This corresponds to an effect size (Cohen's *d*) of 0.96 (95 % CI interval: 0.24 to 1.66). Point estimates and confidence intervals were almost identical when comparing participants in the J-OBE group to controls: mean difference = 6.77 (95 % CI interval: 2.86 to 10.68, *p* = .001), Cohen's *d* = 1.13 (95 % CI interval: 0.44 to 1.81). However, no significant difference was found when contrasting the J-LNR and J-OBE groups (mean difference = 0.00, 95 % CI interval: -4.23 to 4.24, *p* = .998, Cohen's *d* = 0.00, 95 % CI interval: -0.63 to 0.63).

### 2.3.2. Fatigue

Descriptive statistics for this variable at each time point and for each study group are also provided in Table 2. The mixed ANOVA on feelings of fatigue produced a significant group × time interaction, *F*(2, 53) = 4.26, *p* = .019, *η*<sup>2</sup><sub>p</sub> = .13. Follow-up *t*-tests revealed that the difference between the J-LNR and CTRL groups with regard to changes in feelings of fatigue from pre-to post-intervention was statistically significant (mean difference = -4.71, 95 % confidence interval: -8.50 to -0.92, *p* = .0166, Cohen's *d* = -0.87, 95 % CI interval: -1.57 to -0.16). This difference also reached statistical significance when comparing the J-OBE and CTRL groups: mean difference = -5.76 (95 % CI interval:

-9.85 to -1.68), *p* = .007, Cohen's *d* = -0.92 (95 % CI interval: -1.58 to -0.25). No difference was found between the two exercise groups (mean difference = -1.06, 95 % CI interval: -5.73 to 3.61, *p* = .649, Cohen's *d* = -0.15, 95 % CI interval: -0.78 to 0.49).

## 3. Discussion

The purpose of this study was to investigate the effects of a short bout of moderate-intensity jogging on feelings of energy and fatigue, comparing green exercise (jogging in a local natural reserve) to an identical exercise bout in an outdoor built environment, and a sedentary control condition. One of our hypotheses was that participants in the two exercise conditions would exhibit favorable pre-to post-intervention changes in feelings of energy and fatigue (which would not be observed for participants in the sedentary control group). This was largely supported. Consistent with previous research, our results demonstrate that a single bout of exercise, even of short duration (14 min), can significantly increase feelings of energy and decrease feelings of fatigue. Participants in the two exercise conditions showed statistically significant pre-to post-intervention improvements compared to the sedentary control group. These findings align with existing literature (e.g., Loy et al., 2013). The effect sizes observed in our study were substantial, pointing to the potential role of moderate-intensity exercise in revitalizing those
<caption>**Table 2**</caption>

Pre-intervention scores, post-intervention scores, score changes for the POMS-V and POMS-F subscales, and effects sizes (Cohen's *d*) for all possible pairwise comparisons.

<table><thead><tr><th rowspan="2"></th><th colspan="3">Group</th><th rowspan="2">p-value<sup>a</sup></th></tr><tr><th>CTRL (n = 17)</th><th>J-OBE (n = 22)</th><th>J-LNR (n = 17)</th></tr></thead><tbody><tr><td><strong>POMS-V</strong></td><td></td><td></td><td></td><td>.003</td></tr><tr><td>pre-intervention</td><td>14.53 (6.72)</td><td>14.68 (5.54)</td><td>14.71 (8.26)</td><td></td></tr><tr><td>post-intervention</td><td>11.94 (7.72)</td><td>18.86 (5.98)</td><td>18.88 (3.79)</td><td></td></tr><tr><td>score change</td><td>-2.59 (6.57)</td><td>+4.18 (5.49)</td><td>+4.17 (7.57)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-LNR vs. J-OBE: 0.00 (-0.63, 0.63)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-LNR vs. CTRL: 0.96 (0.24, 1.66)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-OBE vs. CTRL: 1.13 (0.44, 1.81)</td><td></td></tr><tr><td><strong>POMS-F</strong></td><td></td><td></td><td></td><td>.019</td></tr><tr><td>pre-intervention</td><td>9.76 (8.45)</td><td>9.09 (7.45)</td><td>8.35 (7.52)</td><td></td></tr><tr><td>post-intervention</td><td>12.12 (8.17)</td><td>5.68 (5.31)</td><td>6.00 (5.47)</td><td></td></tr><tr><td>score change</td><td>+2.35 (3.95)</td><td>-3.41 (7.54)</td><td>-2.35 (6.58)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-LNR vs. J-OBE: -0.15 (-0.78, 0.49)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-LNR vs. CTRL: -0.87 (-1.57, -0.16)</td><td></td></tr><tr><td></td><td colspan="3">Cohen's d comparing J-OBE vs. CTRL: -0.92 (-1.58, -0.25)</td><td></td></tr></tbody></table>

Note. All values presented are means and standard deviations in brackets, or estimated Cohen's *ds* with 95 % confidence intervals in brackets. J-LNR: jogging in a local nature reserve; J-OBE: jogging on a cinder track in an outdoor built environment; CTRL: sedentary control group.

<sup>a</sup> *p*-values represent group × time interaction effects (determined via mixed 3 x 2 ANOVA tests).

who feel exhausted or overwhelmed.

Now, our main hypothesis stated that improvements in feelings of energy and fatigue would be more pronounced among participants who exercised in the local nature reserve. This was not supported. Contrary to our hypothesis, the type of outdoor environment in which the run took place had no influence. Several explanations may possibly underlie this negative result.

First, forest volatile organic compounds (FVOCs) which have been shown to induce mood improvements (including energy boosts) in individuals exposed to forest environments (e.g., Kennedy et al., 2011) are primarily emitted during the spring and summer months. The lack of additional benefits for exercise in a forest observed in the present study could be attributed to reduced FVOCs concentrations at the time of study completion (second half of the fall season). Indeed, in western European forests, tree defoliation usually occurs during fall and winter, involving the shedding of leaves from deciduous trees and a decline in overall vegetation activity. Consequently, the emission of FVOCs may be diminished during fall and winter, potentially attenuating the documented physiological and psychological benefits associated with forest environments. Future research should investigate seasonal variations in FVOCs concentrations and their relationship with feelings of energy and feelings of fatigue during exercise in natural environments to further elucidate the mechanisms underlying the psychological benefits of green exercise.

Second, some authors have proposed that, in contrast to urban or indoor environments, natural environments provide the individual with more opportunities for action and sensorial experiences, which may explain the unique mood-enhancing effects of green exercise compared to exercise in other environments (e.g., Araujo et al., 2019). This assertion is primarily based on affordance theory (Gibson, 2014) according to which the environment plays a crucial role on psychological well-being by providing more or less opportunities for engagement and restoration. In natural environments, the sounds of birds, the visual complexity and beauty of plants, and the tactile sensations of different natural materials are all affordances that are experienced directly and vividly by the individual. One reason why 14 min of moderate-intensity exercise in a local nature reserve did not produce higher revitalization than in an urban environment in the present study may be because the

duration of the run was too brief to allow participants to fully appreciate the natural beauty and complexity, engage with, and benefit from the natural surroundings. Another reason is that the immediate physiological responses to exercise, such as increased heart rate and breathing, could have overshadowed the subtle restorative effects of nature. Still another reason could relate to personal preferences and interest, such as nature connectedness. Nature connectedness refers to the extent to which individuals feel a sense of belonging to the natural world. It encompasses one's cognitive, affective, and experiential connection with nature, influencing how one perceives and interacts with natural environments (Martin & Czellar, 2016). Presumably, individuals with a high degree of nature connectedness are more likely to be more mindful and present during green exercise. This heightened engagement can lead to a more profound and enjoyable experience, thus amplifying the mood-enhancing benefits of green exercise compared to those with lower nature connectedness. Although nature connectedness was not measured in the present study, it could be speculated that our sample (which included participants aged 19–23) may exhibit low levels of nature connectedness, which might account for our failure to observe higher benefits in the green exercise condition. Indeed, Hughes et al. (2019) found age-related patterns for nature connectedness, with connection declining from childhood to the early 20s. Future studies should include such baseline assessments to address this question.

Some limitations should be considered when evaluating the results of our study. First, even though efforts have been made to standardize exercise intensity for participants in the two exercise groups, recent studies have expressed concerns regarding the use of age-predicted maximal heart rate as a valid measure of exertion (e.g., Arena et al., 2016). Using intensities based on the ventilatory equivalents for oxygen and carbon dioxide or based on blood lactate measurements is preferable (e.g., Jannick et al., 2020). However, these methods require cumbersome equipment that may interfere with natural breathing (exercise-testing mask) or disrupt the exercise session (blood collection for lactate determination). By contrast, heart rate monitors are convenient to wear and easy to check anytime while exercising, allowing individuals to adjust their exercise intensity on the spot. A second limitation is that participants in the control group were instructed not to fall asleep. In response to such an instruction, participants may have guessed what the hypothesis was, or may have responded that they were more fatigued just because they were primed to feel sleepy. Third, social interactions among participants were allowed in each of our study group, but no objective measure of their pattern or intensity was assessed. Further studies including such measures are needed since, in addition to greenness, social interaction has been found to be strongly involved in raising mood and energy levels during everyday life physical activity (e. g., Bollenbach et al., 2022). This could be realized using the SOSIP protocol recently proposed by Chen et al. (2023) for instance. A fourth limitation is the use of self-report measures to assess feelings of energy and fatigue, which may be subject to bias or inaccuracies. Future studies should incorporate objective measures or physiological indicators of energy and fatigue. We may also recommend research using ecological momentary assessments (EMA) methodologies since it has been demonstrated that multiple assessments of mood for each participant allow for higher-power analyses (Degroote et al., 2020; Hartson et al., 2023). In addition, EMA assessments of mood allow the investigation of how people feel during and/or following physical activity occurring throughout their daily lives. A final limitation is that our sample consisted of young, physically active university students, limiting the generalizability of our results to other populations. Future research should replicate and extend our findings in more diverse samples.

In conclusion, the present study failed to demonstrate that a short bout of moderate-intensity exercise in a natural environment has more powerful revitalizing effects than an identical exercise session in an urban setting. Both participants who jogged in a nature reserve and those who jogged on a cinder track in an outdoor built environment reported significant improvements in feelings of energy and feelings of
fatigue following exercise in contrast to participants who watched an educational video. Though future research is needed to clarify the mechanisms involved, it is suggested that this null finding is due to the low metabolic activity of trees and other plants at the time our study was conducted.

## Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

## Data sharing statement

Raw data for this study are available on reasonable request from the corresponding author (fabien.legrand@univ-reims.fr).

## CRediT authorship contribution statement

Fabien D. Legrand: Writing – original draft, Supervision, Methodology, Formal analysis, Conceptualization. Philippe Jeandet: Writing – original draft, Validation. Guillaume Polidori: Methodology, Data curation. Fabien Beaumont: Visualization, Formal analysis. Ryan E. Rhodes: Writing – original draft, Validation.

## Declaration of competing interest

The authors declare no conflict of interest regarding this study.

## Data availability

Data will be made available on request.

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