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. 2025 Nov 19;25(12):e70072. doi: 10.1002/ejsc.70072

Effect of Two Types of Open‐Skill Training on Cognitive Functions: The Case of Parkour

Sidney Grosprêtre 1,2,3,✉, Alexis Chotel 1,2, Célia Ruffino 1
PMCID: PMC12629852  PMID: 41261364

ABSTRACT

The positive impact of physical activity on cognitive functions is well established and varies by exercise type, with open‐skill sports—activities involving high uncertainty—offering distinct advantages. Although team sports are traditionally considered open‐skill activities, parkour provides a dynamic and varied environment. This study compared the effects of indoor team sports (consistent environment) and parkour (varied environments) on cognitive functions. Forty healthy young adults (mean age: 21.5 ± 3 years) were divided into a team sports group (TS, n = 19) and a parkour group (PK, n = 21). Both groups trained twice a week for 4 weeks, with sessions lasting 2 hours each. Cognitive performance was assessed pre‐ and posttraining using the Trail Making Test (TMT), Letter Cancellation Test (LCT), Change Blindness Test (CB), visual memory tests, and short‐ and long‐term memory recall. The PK group significantly improved in TMT and CB tests (p < 0.001), whereas the TS group showed no significant changes (p > 0.05). Both groups improved similarly in the LCT and working memory tests (p < 0.001). However, the PK group outperformed the TS group in long‐term memory tasks (p < 0.001). These findings suggest that parkour's exploratory nature enhances observation skills, visuospatial attention, and long‐term memory more effectively than indoor team sports. Training in diverse environments appears to yield greater benefits for visual and cognitive capacities than practice in static settings.

Keywords: attention, executive functions, inhibition, memory, parkour

Highlights

  • Four weeks of parkour training improved visuospatial attention and cognitive flexibility

  • Parkour participants showed faster change detection and enhanced observation skills

  • Parkour training led to better long‐term memory retention than team sport practice

  • Cognitive gains were linked to adapting to varied and unpredictable training environments

1. Introduction

Physical activity and sport are widely recognized as essential for health, with prevention campaigns encouraging people of all ages, from children to the elderly, to engage in regular physical activities. Beyond improving physical health (Pate et al. 1995) and reducing the risk of diseases, such as cardiovascular conditions (Isath et al. 2023) and cancer (McTiernan et al. 2019), there is growing interest among scientists and healthcare professionals in the impact of physical activity on mental health (Paluska and Schwenk 2000) and cognitive functions (Hötting and Röder 2013).

Cognitive functions encompass mental processes such as perception, attention, memory, reasoning, and executive functions (Lezak 2004). Research increasingly highlights the positive effects of physical exercise on these processes. For instance, studies show that individuals with higher fitness levels or regular physical activity exhibit better cognitive performance than their less active peers (Chaddock et al. 2011; Furley et al. 2013; Chang et al. 2017). Additionally, physical activity has been linked to improvements in inhibitory control, problem‐solving, cognitive flexibility, and visuospatial attention (Gentile et al. 2020; Bidzan‐Bluma and Lipowska 2018).

Notably, the type of physical activity plays a crucial role. For example, Coetsee and Terblanche (2017) found that strength training and moderate aerobic training were more effective than high‐intensity aerobic training for improving cognitive functions in older adults. Similarly, resistance training has been shown to protect against cognitive decline by preserving executive planning and working memory (Bherer et al. 2013).

Beyond the physical characteristics of exercise, the nature of the activity itself plays a crucial role in shaping both physical and cognitive outcomes. In sports science, activities are commonly classified along a continuum ranging from closed‐skill to open‐skill sports. Closed‐skill sports, such as track and field, swimming, or gymnastics (Grosprêtre and Gabriel 2021; Gu et al. 2019; Gu et al. 2019), are typically performed in stable and predictable environments, where motor actions are largely predetermined and repetitive, emphasizing technical precision and physical conditioning. In contrast, open‐skill sports, including team and racket sports (Gu et al. 2019) as well as parkour (Grosprêtre and Gabriel 2021), unfold in dynamic and unpredictable environments. Athletes must constantly adapt to external stimuli, such as opponents, teammates, moving objects or environmental changes, requiring continuous perceptual‐motor integration, attentional control, working memory, and decision‐making (Gu et al. 2019). This higher cognitive engagement is thought to explain why open‐skill sports more consistently enhance cognitive functions than closed‐skill sports across children and adolescents (Möhring et al. 2022; Schmidt et al. 2015; Shi et al. 2022; Tsai et al. 2012), young adults (Chueh et al. 2017; Koch and Krenn 2021; Krenn et al. 2018; Wang et al. 2013), and elderly populations (Li et al. 2019; Tsai et al. 2016, 2017). These improvements typically concern executive functions, visuospatial ability, and memory (Gu et al. 2019) and are supported by the unpredictable nature of open‐skill environments, which may stimulate neuroplasticity through continuous reorganization in response to novel and complex challenges (Gu et al. 2019; Lai et al. 2024).

Furthermore, although team sports (e.g., basketball and soccer) and racket sports (e.g., tennis and badminton) are usually considered as open‐skill sports by excellence, other booming activities, such as parkour, may offer an infinite variety of environments and present a strong potential for enhancing cognitive performance. Emerging activities, such as parkour, might do fall under open‐skill sports due to the infinite variety of environments and the high level of adaptability required as compared to gymnastics for instance (Grosprêtre and Gabriel 2021). Parkour, a modern physical discipline, involves navigating obstacles in various environments, often urban, using one's physical and motor skills (Grosprêtre and Lepers 2016). Unlike traditional sports, parkour is considered a “lifestyle sport,” free from rigid rules and standardization, fostering creativity and adaptability (Pagnon et al. 2022). However, the role of environmental variability has not yet been thoroughly investigated within the debate on the benefits of closed‐ versus open‐skill activities. This study proposes a novel and more nuanced approach by comparing different forms of open‐skill activities that vary in their degree of environmental unpredictability. This study aimed to compare the cognitive benefits of two open‐skill activities: indoor team sports (conducted in consistent environments) and parkour (conducted in varied environments). Forty healthy young participants were divided into two groups and underwent a 4‐week training program. We hypothesized that the parkour group would show greater improvements in specific cognitive functions, particularly visuospatial attention and observational skills, due to the greater variety and unpredictability of their practice environments.

2. Methods

2.1. Participants

Forty healthy young participants (age: 21.5 ± 3 years old; stature: 174 ± 8 cm, body mass: 66.9 ± 10 kg, 16 women, and 24 men) gave written informed consent to participate in the study. None of them reported neurological or physical disorders or psychiatric or addictive comorbidities. All the participants were novices in parkour and in all the other tested activities but were recreationally active (2.5 ± 0.7 h of activity per week) with various physical activities. The study protocol was approved by the local ethic committee and conducted in accordance with the latest version of the Declaration of Helsinki.

Participants were randomly assigned to two subgroups, one group who practiced various physical activities during the protocol (team sport group, TS) and one group who was specifically trained in parkour (parkour group, PK). The TS group was constituted of 19 participants (age: 21 ± 0.7 years old, height: 177.4 ± 7.5 cm; weight: 67.8 ± 9.7 Kg; and BMI: 21.5 ± 2.4 Kg/m2, 6 women), whereas the PK group was constituted of 21 participants (age: 22.4 ± 6.5 years old, height: 171.6 ± 9 cm; weight: 65.8 ± 11.9 Kg; and BMI: 22.2 ± 2.7 kg/m2, 10 women).

2.2. Experimental Design

All participants first attended a familiarization session designed to train them in the cognitive tests. This helped minimize the learning effect caused by repeated testing throughout the protocol. A minimum of 48 h after the familiarization session, participants returned to the laboratory for their PRE measurements. They then completed a 4‐week training program consisting of two training sessions per week, each lasting 2 hours, with at least one rest day between sessions (e.g., Monday and Wednesday or Tuesday and Thursday).

Each participant was asked to rate their perceived exertion using a 10‐point scale (CR‐10) 10 min after the end of each training session. This allowed the calculation of internal workload based on session duration (FOSTER et al. 2001) and enabled comparison of the total training load between groups. The internal training load for each session was calculated as the product of session duration (in minutes) and the perceived exertion rating. After the final training session, participants returned to the laboratory for POST measurements.

Participants were randomly assigned to one of two training groups:

Team Sport Group (TS): The TS group participated in two training sessions per week involving various collective ball games (e.g., volleyball, football, and basketball). The primary criterion was to practice different activities but always in the same training room. All game rules were already known to participants as confirmed via a questionnaire during the familiarization session. After a common standardized warm‐up, each training session was designed for one specific activity (volleyball, football or basketball). The first part of the session (a third) was dedicated to isolated exercises to train specific skills (ball catching, throwing, and running with the ball). Then, the rest of the session was composed of games, either modified or full‐sized.

Parkour Training Group (PK): The PK group trained exclusively in parkour during two weekly sessions. This involved overcoming obstacles in various urban environments (Pagnon et al. 2022). Care was taken to vary the training environments, with participants visiting eight different urban locations (one unique location per session). Training focused on environment exploration, creativity, and adaptation. Although participants were taught obstacle‐overcoming techniques, a significant portion of each session was dedicated to allowing them the freedom to create their own paths within the new environment.

2.3. Cognitive Tests

Before and after each training period, all participants underwent the same testing procedure, involving a battery of cognitive tests. These tests were selected since they target specific cognitive functions that were shown to be modulated by open‐skills activities (Gu et al. 2019). Some of those tests were already used in previous experiments comparing parkour to other open‐skill or close‐skill sports, such as the change‐blindness paradigm (Grosprêtre and Gabriel 2021), used to compare parkour athletes with practitioners of other disciplines (e.g., climbing and gymnastics), and revealing some interesting differences. Therefore, it made sense in the present work to include this paradigm again to examine whether training novices in parkour would lead to improvements in this capacity.

The tests were performed in random order (intersessions and interparticipants), in a quiet room, in a sitting position. Before and after each testing session, subjective feeling of fatigue has been asked to the participants to ensure similar state between the two measurements times (PRE and POST). This was done by using the Brunel Mood Scale (BRUMS; Terry et al. 2003) to quantify the subjective feeling of fatigue and vividness before and after each testing session. Only the four items related to fatigue (exhausted, sleepy, tired, and worn‐out) and the four related to vigor (active, alert, energetic, and lively) were considered (Marcora et al. 2009). Participants were asked to rate each item on a five‐point scale (0 = not at all, 1 = a little, 2 = moderately, 3 = quite a bit, and 4 = extremely). The Owen–Anderson questionnaire of mood was also fulfilled before each testing session (i.e., in PRE and POST) to account for the global mood state at the time of the measurement.

Particular care was taken in performing the PRE and POST tests at the same moment of the day to avoid the influence of circadian rhythms on cognitive performances (García et al. 2012). The cognitive tests were as follow:

Trail making test (TMT): The part B of the TMT was performed to assess visuospatial attention and cognitive flexibility (Pellegrini‐Laplagne et al. 2022). On a sheet of paper (A4 format), participants had to connect circles that contained letters and numbers in alphabetical and numerical order from A to Z and 1 to 26 in the following manner: 1‐A‐2‐B‐3‐C, etc. The number of correct circles connected in a fixed time of 30 s was considered.

Letter cancellation test: This test allowed to test for selective attention. Participants had to spot the “q” letter among a whole sheet of A4 paper containing 30 lines of “p” letters (total of 1300 characters). A total of 15 “q” letters were randomly placed on the sheet. Participants had to spot as many “q” letters in 10 s by crossing them out, the total number spotted representing the final score.

Change blindness: This test is used to assess observation capacities of participants (Grosprêtre and Gabriel 2021; Loussouarn et al. 2011; Rensink 2009). Sitting in front of a computer screen, participants had to spot changes between pairs of apparently similar images displayed alternatively at high frequencies. These pairs depicted the same picture but containing a single modified detail. Changes were randomly distributed in each picture, calibrated to represent maximum of 10% and 15% of the total image area. Each image of each pair was displayed for 240 milliseconds, interspersed with a gray mask lasting 120 milliseconds. Participants were instructed to press a button as soon as they spotted the change. Then, they had to write the change observed, allowing to ensure afterward that they found the right clue. Ten pairs of images were displayed for each testing session, with one single change by pair that might appear in any part of the picture. Each trial consisted of displaying the two images of the same pair (the original and the modified one) in an alternating manner during a maximum period of 40 s. The search time (i.e., the time between the onset of the changed image and the participant's button press) was accounted. If no change was detected within the 40 s, the trial was considered unsuccessful. The number of unsuccessful trials was also analyzed.

Immediate recall: This test was used to assess verbal memory and short memory of the participants. They were sat in front of a computer showing in one image a list of 15 words, displayed in three columns of 5 words, for 30 s. After these 30 s, the list disappeared and participants had to write on a paper reproducing the configuration of the list (i.e., 3 columns of 5 words) as many words as they can recall for 1 minute. The exact words as well as their positions in the list were asked. Different lists were proposed in‐between participants and in‐between testing sessions. The score for this test was calculated as follow: a right word earns one point, and if the word in in right position, it is an extra‐point. Then, for 15 words, the maximum score is 30.

Delayed recall: This test aimed at evaluating long‐term memory after the training period. In posttests, that is., after 4 weeks of training, participants were asked to recall the list of 15 words displayed in pretest, without reviewing it beforehand. The score was calculated similarly to immediate recall test.

Visual memorization: This test was performed to evaluate both short‐term memory and observation that does not rely on language skills. Pictures were displayed on a screen in front of participants for 30 s. Each picture depicted neutral environments (urban landscapes) without any human beings. After each picture observation, participants were asked five questions in a random order, regarding 5 parts of the picture (upper right and left, lower right and left, and center corresponding to foveal vision). Questions were related to color or form of an element present in the picture (“color of the car”, etc), and were all multiple choices with always the same three possible answers: “yes”, “no,” or “don't know”.

2.4. Data and Statistical Analysis

Display of computerized test and data collection was achieved using E‐prime 2 software (Psychology Software Tools, Pittsburgh, USA). All data are presented as the mean ± standard deviation. Each test was considered separately. The normality of the datasets was verified by the Shapiro–Wilk test and variance homogeneity by the Levene’s test. Each raw predata and postdata have been analyzed as well as the pre–post gain for each group, calculated in percentage as follows: [(POST‐PRE)/PRE] *100. Two‐way repeated analysis of variance (ANOVA) measures were used to assess differences between the raw results of the different tests with factors of time (PRE and POST) and group (PK and TS). Partial‐eta‐squared (η p 2) was calculated from ANOVA results, with values of 0.01, 0.06, and above 0.14 representing small, medium, and large differences, respectively (Cohen 1992). In case of a significant effect, a post hoc test with Bonferroni correction was performed. Between groups differences in gains (percentages) were analyzed using two‐tailed t‐tests. For other comparison, such as training load, two‐tailed t‐tests were also applied. Statistical analysis was performed using JASP software (version 0.13, JASP Team (2020), University of Amsterdam). The level of statistical significance was set at p < 0.05.

3. Results

The mean internal training load of training session was 360.2 ± 49.4 (A.U.) for the TS group and 364.2 ± 75.1 for the PK group and did not differ significantly (p = 0.501). For each group, no significant differences were found in the scores of subjective feelings of fatigue and vigor, assessed before each testing period (PRE and POST). As well, score of global mood state (Owen‐Andersen questionnaire) was not different between the two testing moments. For all cognitive tests, ANOVAs did not reveal any differences in PRE value between groups.

All results of tests relying on attention are displayed in Figure 1. A significant group × time interaction was found on the Trail Making Test score (F1,38 = 7.005, p = 0.012, and η p 2 = 0.156). The PK group increased their score significantly (p < 0.001) wheeas the TS group did not (p = 0.057). Performance was significantly different in POST between TS and PK (p = 0.033). Gains were significantly different (p = 0.031) between groups (Figure 1). A significant group × time interaction was also found for Change Blindness searching time (F1,38 = 4.600, p = 0.038, and η p 2 = 0.108). PK group significantly improved their time (p < 0.001) whereas the TS group did not (p = 0.632). PRE–POST searching times were significantly different between PK and TS (p = 0.032). Regarding the Letter Cancellation Test, a main effect of time was found (F1,38 = 26.077, p < 0.001, and η p 2 = 0.407), but no significant group × time interaction was found (F1,38 = 2.861, p = 0.099, and η p 2 = 0.070). Gains were not significantly different (p = 0.101).

FIGURE 1.

FIGURE 1

Open in a new tab

Effect of parkour and team sport training on attention tests. Average values (± SD) of each attention test, with pre–post performances presented on the left plots, and percentages of change between pre–post performance on the right plots. Dots represent individual's data. White diamonds represent significant differences between PK and TS groups following post hoc analyses. Black triangles represent significant different pre–post gains between PK and TS groups.

No significant interaction (F1,38 = 0.429, p = 0.516, and η p 2 = 0.011) was found on working memory test (instant recall of words). However, a main time effect was found (F1,38 = 24.348, p < 0.001, and η p 2 = 0.391). Both groups increased their capacity to recall words but at a similar extent (Gains of + 23.0 ± 27.7% of words recalled for the TS group, + 23.4 ± 19.7% for the PK group, and p = 0.653).

However, Time × Group interaction was found on long term memory as assessed by delayed recall (F1,38 = 61.075, p < 0.001, and η p 2 = 0.616), that is., the number of words of the PRE‐tests’ list recalled after the whole training (in POST‐tests). Long term memory was differently affected in both groups, participants of the PK groups remembering more words than TS group (Figure 2). Gains were indeed different (p < 0.001), PRE–POST differences being lower in PK than in TS, meaning that PK lost less words. Regarding memory related to picture observations, no interaction was found between factor time and group (F1,38 = 0.616, p = 0.437, and η p 2 = 0.016). Nonetheless, a main time effect was found (F1,38 = 122.496, p < 0.001, and η p 2 = 0.763), showing that both groups increased their scores in picture observation after training but at similar extent (Figure 2). No difference was found between PK and TS regarding gains (p = 0.503).

FIGURE 2.

FIGURE 2

Open in a new tab

Effect of parkour and team sport training on memory tests. Average values (± SD) of each memory test, with pre–post performances presented on the left plots, and percentages of change between pre–post performance on the right plots. Dots represent an individual's data. White diamonds represent significant differences between PK and TS groups following post hoc analyses. Black triangles represent significant different pre–post gains between PK and TS groups.

4. Discussion

In the current study, we examined the impact of two types of open‐skill practice on cognitive functions: one of the most described in sports and scientific literature, that is., indoor team sports, and a booming activity practiced in various environments, that is., parkour. Before and after 4 weeks of practice in either indoor team sports (TS group) or parkour (PK group), both groups were tested on attention (Trail Making Test, Change Blindness, and Letter Cancellation) and memory (working memory, long‐term memory, and visual working memory). Our findings showed significant performance improvement for the first two attention tests only in the PK group, whereas for memory, only long‐term memory discriminated between the two open‐skill practices, favoring PK practice.

Over the past decade, research consistently showed that open‐skill sports, such as team or racket sports, yield greater improvements in cognitive functions than closed‐skill sports across children, young adults, and older populations (Möhring et al. 2022; Koch and Krenn 2021; Li et al. 2019). These benefits mainly concern executive functions, visuospatial ability, and memory (Gu et al. 2019) and were attributed to the constant adaptation and higher cognitive demands imposed by dynamic and unpredictable environments (Gu et al. 2019; Lai et al. 2024). These aspects are prominent in the types of open‐skill activities tested in our study, that is., team sports and parkour. Indeed, team sports involve an uncertainty regarding opponent team's reactions, which leads to an infinite variety of responses toward the game in an externally paced environment (Di Russo et al. 2010; Di Russo et al. 2010). Regarding parkour, openness of practice is induced by the infinite variety of obstacles offered by constant changes of urban environments (Grosprêtre and Gabriel 2021).

In previous literature, open‐skill sports were often studied through opposition sports, either one‐on‐one (e.g., racket sports; Hung et al. 2018; Takahashi and Grove 2019; Tsai et al. 2017) or team sports (Madinabeitia‐Cabrera et al. 2023; Schmidt et al. 2015). Here, we sought to compare cognitive abilities in sports involving open‐skill activities in the same environment (team sports) and in various environments (parkour). Although team sports practice did not yield significant improvements in cognitive performance, the results of parkour practice partially align with existing literature on open‐skill sports. Specifically, parkour training enhanced several cognitive capacities, including visuospatial attention and cognitive flexibility (as measured by the Trail Making Test), observation capacities (evidenced by reduced change blindness search time), and long‐term memory (evaluated through delayed recall).

Behavioral explanations for these improvements in cognitive functions following open‐skill sports, such as the higher cognitive demands involved, are supported by studies investigating underlying neural processes. For example, Hung et al. (2018) found higher levels of BDNF, a neurotrophic factor contributing to neural plasticity, after 30 min of badminton (open‐skill) practice compared to running (closed‐skill), suggesting BDNF mediates improvements in cognitive flexibility in open‐skill sports. Similarly, electroencephalography (EEG) studies have shown greater P300 amplitude (Tsai and Wang 2015) and shorter Error‐Related Negativity (ERN) latency (Li et al. 2019) following open‐skill practices, both parameters linked to cognitive improvements. These findings support the observed benefits of parkour practice on cognitive flexibility, observation capacities, and long‐term memory.

Interestingly, performance improvements in attention were only observed after parkour practice, while previous studies demonstrated positive effects from team sports. Two explanations may account for this discrepancy. First, unlike team sports, which were conducted in a consistent gymnasium environment, parkour involved constant changes in environment, requiring participants to (1) learn to interpret their surroundings and (2) adapt their skills to new settings (Pagnon et al. 2022). Second, parkour represented a completely new activity for participants. The motor learning involved in parkour is cognitively demanding, stimulating neural plasticity. This challenge was further heightened by the constantly changing environments and obstacles from one session to the next. In contrast, although team sports are also challenging for the brain as showed, for example, after volleyball training (Zhang et al. 2024), here the team sports activities, being more familiar (e.g., ball games), relied more on established motor routines for the tested population.

The “open” nature of sports activities can be considered in two ways: (1) variability in the practice environment, requiring environmental reading and adaptation (e.g., parkour or climbing; Grosprêtre and Gabriel 2021) or (2) variability in game situations, requiring interaction with opponents (e.g., racket sports (Gallotta et al. 2020), boxing (Pujari 2024), or team sports (Madinabeitia‐Cabrera et al. 2023). Parkour aligns with the first category and can be compared to other outdoor activities such as climbing or trail running. These activities rely on interacting with the environment as a tool for practice, enhancing observation capacities (e.g., use of cliff's asperities to climb). In that way, it was previously shown that parkour and climbing promoted better observation capacities than gymnastics for instance as evaluated by the Change Blindness paradigm (Grosprêtre and Gabriel 2021). In parkour, this is amplified by using urban environments not designed for training. Novices must creatively reinterpret common urban structures (e.g., walls, barriers, and benches) as obstacles and adapt their motor behavior according to the opportunities perceived in relation to their action capabilities. In fact, perception of one's environment also depends on the possibilities to act within it (Witt et al. 2011, 2012). This process, linked to Gibson's (1979) concept of “affordances”, involves perceiving and acting on environmental opportunities, enhancing environmental perception and cognitive functions. Affordances define the range of actions an object or an environment allows based on one's perception. The more a person interacts with and evolves within an environment, the more affordances are created, thereby enhancing their perception of that environment. In climbing, the level of expertise is directly linked to the number of affordances generated by the practitioner when facing a new environment (Seifert et al. 2021). The creative process and the development of alternative solutions to achieve the same goal (e.g., finding different ways to jump over a bench) are central features in parkour (Pagnon et al. 2022). Therefore, the creation of new affordances represents a significant challenge for the brain throughout the training process.

Finally, this study presents some limitations and perspectives. A control group without physical activity would have helped isolate the effects of practice itself, by providing an overview of changes in the cognitive abilities tested induced by daily‐life activity regardless of sport practice and by accounting for potential test–retest effects between pre and postassessments. Additionally, testing other open‐skill (e.g., individuals such as racket sports) or closed‐skill sports could clarify the impact of activity type. This also constitutes a limitation of the present study, since team sports and parkour have different demands on perception and adaptability as the former requiring interactions with teammates and opponents, and the latter focusing on individual navigation in urban environments. In addition, since participants were novices in both activities, potential effects related to unfamiliarity with parkour could be likely minimized. The short training duration (4 weeks) may also have limited observed effects as previous studies used longer programs (e.g., Tsai et al. 2017). Future research could also integrate neurophysiological measures, such as EEG, to assess changes in P300 amplitude and ERN latency, useful to understand the underlying mechanisms of sport‐related cognitive enhancement (Li et al. 2019; Tsai and Wang 2015). In the present study, as in previous ones, cognitive capacities were assessed using standardized laboratory tests. To better evaluate the impact of various sports on cognitive functions, it would be valuable to extend research to field tests, assessing, for instance, cognitive capacities in dual‐task scenarios. As an example, there exists an active version of the Trail Making Test that involves a whole‐body visuospatial recognition of a sequence of numbers and/or letter. This test, called the Trail Walking Test (Schott 2015) lead participants to walk as fast as possible along a path of cones with alternating numbers and letters in a wide space (e.g., a square of 4 × 4 meters), involving a dual task with both physical and cognitive demands. This test has been used for example to test visuospatial recognition and flexibility in soccer players in a dual‐task manner (Klotzbier and Schott 2024; Klotzbier and Schott 2024)

To conclude, this study, together with existing literature, supports the idea of a continuum between open‐ and closed‐skill sports. Activities situated toward the open‐skill end of this continuum appear to foster cognitive performance improvements, potentially through enhanced neural plasticity, driven by the constant reorganization and adaptation of the brain. However, because neural plasticity and brain reorganization were not directly assessed, such mechanisms remain speculative and should be explored in future work using neuroimaging approaches, especially in parkour. At the same time, the present article highlights the importance for parkour practitioners to vary their training environments. Doing so can sharpen their ability to interpret complex surroundings, improve attentional focus, and enhance risk awareness, especially when practicing at height or in environments shared with pedestrians, vehicles, and other potential hazards. Overall, training in diverse and unpredictable settings not only enhances physical adaptability but also cultivates cognitive functions such as spatial awareness, attentional control, cognitive flexibility, and possibly even long‐term memory consolidation. Beyond the scope of sport, these findings have important implications for rehabilitation and therapeutic interventions, where practice conditions are often repetitive and predictable. Introducing more variability and elements of open‐skill practice could provide a powerful means of stimulating cognitive processes and promoting neural recovery. In this sense, parkour exemplifies how engaging with complex, dynamic environments may contribute to both athletic performance and broader applications in health and rehabilitation.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

The authors have nothing to report.

Grosprêtre, Sidney , Chotel Alexis, and Ruffino Célia. 2025. “Effect of Two Types of Open‐Skill Training on Cognitive Functions: The Case of Parkour,” European Journal of Sport Science: e70072. 10.1002/ejsc.70072.

Funding: The authors received no specific funding for this work.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

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