Nicolas Mascret
email: nicolas.mascret@univ-amu.fr

Gilles Montagne

Antoine Devrièse-Sence

Alexandre Vu

Richard Kulpa

Acceptance by athletes of a virtual reality head-mounted display intended to enhance sport performance

Keywords: Virtual environment, technology acceptance model, training, simulation, competition

While a growing number of studies have highlighted the potential of virtual reality (VR) to improve athletes' skills, no research has yet focused on acceptance of a VR headmounted display (VR-HMD) designed to increase sport performance. However, even if technological devices could potentially lead to performance improvement, athletes may not always accept them. To investigate this issue, the Technology Acceptance Model (TAM) examines if perceived usefulness, perceived ease of use, perceived enjoyment, and subjective norms (i.e., social influence) are positive predictors of intention to use a specific technology.

The aims of the present study were to test with competitive athletes the validity of the TAM before a first use of a VR-HMD intended to enhance sport performance and to examine to what extent the level of practice and the type of sport practiced have an influence on the previous variables of the TAM. The study sample comprised 1162 French athletes (472 women, 690 men, Mage = 24.50 ± 8.51 years) who usually practiced a sport in competition (from recreational to international level). After reading a short text presenting the VR-HMD and its interests for sport performance, the participants filled out an online questionnaire assessing their acceptance of this technological device before a first use. The results of the structural equation modeling analysis revealed that perceived usefulness, perceived ease of use, perceived enjoyment, and subjective norms were positive predictors of intention to use this VR-HMD, validating the suitability of the TAM for investigating the acceptance by athletes of a VR-HMD designed to increase their sport performance. The results also showed that athletes of all sport levels (a) had a significant intention to use VR, (b) found it quite useful (except for recreational athletes), quite easy to use, and quite pleasant to use, even if their entourage would not encourage them to use it (except for international athletes), and (c) found the VR-HMD easy and pleasant to use whatever the sport practiced. Notably some athletes (e.g., triathletes, swimmers, cyclists) did not find the VR-HMD significantly useful and did not have significant intention to use it to increase their performance. Identifying acceptance by athletes of such a device may increase the likelihood that it will be used by athletes of different levels and from different sports, so that they can benefit from all its advantages related to the improvement of their sport performance. Needs-based targeted interventions may also be conducted toward athletes who might be reluctant to integrate this type of device into their training.

Introduction

In many domains, technologies designed to increase performance are growing exponentially. Among the different technologies available, virtual reality (VR) is becoming more and more important in fields as diverse as education [START_REF] Radianti | A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda[END_REF], therapy [START_REF] Cieślik | Virtual reality in psychiatric disorders: A systematic review of reviews[END_REF], surgery [START_REF] Moglia | A systematic review of virtual reality simulators for robot-assisted surgery[END_REF], and rehabilitation [START_REF] Rose | Immersion of virtual reality for rehabilitation-Review[END_REF]). In the sport context, athletes' use of technology has constantly developed over many years (for reviews, see [START_REF] Akbaş | Application of Virtual Reality in Competitive Athletes-A Review[END_REF][START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF][START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF], in the pursuit of competitive advantage and/or health benefits through sport innovation. While the first studies on VR technology have existed since the late 1950s, the term "virtual reality" was popularized in the 1980s [START_REF] Lanier | Virtual reality: The promise of the future[END_REF]. The first works on VR in the sport domain were conducted in the 1990s [START_REF] Carr | Is virtual reality virtually here?[END_REF]. A renewed interest has been observed in recent years for the use of VR in the field of sport, mainly due to the miniaturization of the devices as well as the reduction of the costs associated with their acquisition [START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF]. While the questions related to either the effectiveness of VR for improving sport performance [START_REF] Faure | Virtual reality to assess and train team ball sports performance: A scoping review[END_REF] or the possibility of transferring a skill from VR to real life [START_REF] Gray | Transfer of training from virtual to real baseball batting[END_REF] have already been investigated, the question of athletes' acceptance of a technology as innovative as VR is also inevitably raised. Surprisingly, studies focusing on the latter question are lacking in the sports literature examining immersive VR intended to enhance sports performance. Therefore, the present study investigated the acceptance of this type of technology by athletes of different levels and from different sports.

VR and Sport Performance

Based on an interactive computer-simulated environment, VR induces a sense of being present in another place, either mentally or physically. According to [START_REF] Heeter | Being there: the subjective experience of presence[END_REF] and [START_REF] Sheridan | Musings on telepresence and virtual presence[END_REF], presence is the sense "of being there" in the virtual environment. Presence is a psychological, perceptual, and cognitive consequence of immersion, the latter being related to the objective level of sensory fidelity a VR system provides thanks to its technological characteristics [START_REF] Slater | Taking steps: the influence of a walking technique on presence in virtual reality[END_REF]. Because movement is captured by sensors, the system provides feedbacks to the user who interacts with and/or reacts to the virtual environment. Even online visual feedback for whole body movement may be provided in a computer automatic virtual environment (CAVE), watching one's own performance together with full body superimposition of a skilled performance [START_REF] Hülsmann | Superimposed skilled performance in a virtual mirror improves motor performance and cognitive representation of a full body motor action[END_REF]. VR may also be used for instructional or observational learning purposes (e.g., [START_REF] Watson | Using mixed reality displays for observational learning of motor skills: A design research approach enhancing memory recall and usability[END_REF]. A SWOT analysis [START_REF] Düking | The potential usefulness of virtual reality systems for athletes: a short SWOT analysis[END_REF] focusing on the potential usefulness of VR for athletes highlighted many strengths (e.g., training at any time in everyday real-life settings, biofeedback, repetition of actions, reduced risk of injury, manipulation of the visual environment) and opportunities (e.g., improvement of skills and tactics, motor imagery, preparation for competitions). Athletes may compete against or train with virtual avatars, for instance in rowing [START_REF] Parton | The effects of competitiveness and challenge level on virtual reality rowing performance[END_REF] and in running on a treadmill [START_REF] Nunes | Motivating people to perform better in exergames: Collaboration vs. competition in virtual environments[END_REF]. Manipulating an infinite number of scenarios may also contribute to train athletes in an increasingly individualized manner [START_REF] Hoffmann | Energy management using virtual reality improves 2000-m rowing performance[END_REF]. Some reviews [START_REF] Faure | Virtual reality to assess and train team ball sports performance: A scoping review[END_REF][START_REF] Frank | Virtual reality and mental training[END_REF][START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF][START_REF] Stone | Effectiveness and efficiency of virtual reality designs to enhance athlete development: an ecological dynamics perspective[END_REF] have shown that interactive VR applications provide powerful tools to improve athletes' performance and skills, as well as physiological and psychological outcomes. For example, VR practice produced improvements in putting accuracy in novice golfers [START_REF] Harris | The effect of a virtual reality environment on gaze behaviour and motor skill learning[END_REF], in rowing performance [START_REF] Parton | The effects of competitiveness and challenge level on virtual reality rowing performance[END_REF], in physical exertion when running on a treadmill (Nunes et al., 2014), in anticipation performance in cricket [START_REF] Discombe | Effects of traditional and immersive video on anticipation in cricket: A temporal occlusion study[END_REF], and in mental training [START_REF] Frank | Virtual reality and mental training[END_REF]. Moreover, sport training in VR may improve real-world performance, especially for closed skills [START_REF] Gray | Transfer of training from virtual to real baseball batting[END_REF][START_REF] Michalski | Using virtual environments to improve real-world motor skills in sports: A systematic review[END_REF].

The most immersive VR systems are the CAVE, a large cube with screens which the user physically enters, and the VR head-mounted display (VR-HMD, e.g., HTC Vive, Oculus Rift), a wearable device with a screen that covers the eyes to view the virtual world in stereovision. Even though the CAVE and the VR-HMD are two immersive systems that share the same key features [START_REF] Slater | Place illusion and plausibility can lead to realistic behaviour in immersive virtual environments[END_REF], the present study focused on the VR-HMD because (a) it is becoming increasingly accessible to the public [START_REF] Cherni | Using virtual reality treadmill as a locomotion technique in a navigation task: Impact on user experience-case of the KatWalk[END_REF], (b) its cost is much lower than the CAVE, (c) the VR-HMD is also smaller and very much easier to transport than the CAVE, and (d) its positive influence on motor and sport performance has been validated (Bideau, Kulpa, Vignais, Brault, Multon, & Craig, 2010;Michalski , Szpak, Saredakis, Ross, Billinghurst, & Loetscher, 2019;[START_REF] Rolin | Perception of looming motion in virtual reality egocentric interception tasks[END_REF]. Despite all the previous promising advantages, using VR and especially VR-HMD to enhance sport performance can also have several limitations, such as limited field of view, no direct perception of the user's own body, limited haptic feedback, and limited interaction with physical objects [START_REF] Stone | Effectiveness and efficiency of virtual reality designs to enhance athlete development: an ecological dynamics perspective[END_REF], costs, unsuitability for training some specific sport skills, potential development of unnatural patterns of motion, and even social isolation [START_REF] Düking | The potential usefulness of virtual reality systems for athletes: a short SWOT analysis[END_REF]. At present, VR use has not yet become widespread as part of the optimization of sport performance [START_REF] Akbaş | Application of Virtual Reality in Competitive Athletes-A Review[END_REF]. Therefore, it seems relevant to investigate the potential reasons for this observation. Among these, examining the acceptance of VR by athletes could be a promising perspective.

Acceptance of Technology in the Sport Context

Even if technological devices are effective and validated, they may not always be accepted by potential users. The Technology Acceptance Model (TAM, [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF][START_REF] Venkatesh | A theoretical extension of the technology acceptance model: Four longitudinal field studies[END_REF] is the most widely used model in the literature to explain acceptance of technology, which investigates the psychological determinants that may influence the intention to use a technology, either before or/and after use. The first works conducted with the TAM have highlighted that perceived usefulness of a technology and its perceived ease of use were positive predictors of behavioral intention to use a technology, which is itself a predictor of its actual use [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF][START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF]. Intention to use a technology may also be positively predicted by perceived enjoyment, especially when the technology has a hedonic dimension (van der Heiden, 2004). All the previous variables may also be predicted by subjective norms, which are a particular form of social influence related to the opinions of important others about the individual's potential use of a specific technology [START_REF] Schepers | A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects[END_REF]. Subjective norms were found to be positive predictors of perceived usefulness and intention to use [START_REF] Schepers | A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects[END_REF], but also of perceived ease of use (e.g., Al-Rahmi, Alzahrani, Yahaya, Alalwan, & Kamin, 2020) and perceived enjoyment (e.g., [START_REF] Zhou | Difference between leisure and work contexts: The roles of perceived enjoyment and perceived usefulness in predicting mobile video calling use acceptance[END_REF]. The relationships between the previous variables of the TAM are presented in Figure 1. Actual use is not represented in Figure 1 because the present study focused on acceptance by athletes of a VR-HMD intended to enhance sport performance, before a first use of this device.

At first glance, it may be surprising to investigate the acceptance of a technology before its first use. However, this line of research is widely represented in the TAM literature because it may contribute to a better understanding of the first step leading to the actual rollout of technology [START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF]. It contributes to identify some of the psychological determinants (i.e., perceived usefulness, perceived ease of use, perceived enjoyment, social norms) that could initially block or threaten the intention to use a technology whose effectiveness has been objectively proven. Indeed, any potential user may have an opinion about a technology and the desire to adopt it (or not) when this technology is presented to them only through a photo, a text, a verbal discussion, or a video [START_REF] Li | Health monitoring through wearable technologies for older adults: Smart wearables acceptance model[END_REF]. For instance, this psychological process is particularly widespread in the field of advertising for technological devices (e.g., [START_REF] Prasetyo | Determining Factors Affecting Acceptance of E-Learning Platforms during the COVID-19 Pandemic: Integrating Extended Technology Acceptance Model and DeLone & McLean IS Success Model[END_REF]. Initially, the TAM has hypothesized that perceived usefulness and perceived ease of use were predictors of attitude towards a technology, the latter then predicting the intention to use it [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF]. But it is now commonly accepted (for a review, see [START_REF] Turner | Does the technology acceptance model predict actual use? A systematic literature review[END_REF] that the attitude construct is unnecessary in the TAM. Initial opinion before a first use may directly influence intention to use a technology and its actual use, as predicted by the evolution of the TAM's theoretical framework [START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF][START_REF] Venkatesh | A theoretical extension of the technology acceptance model: Four longitudinal field studies[END_REF]. Of course, this initial opinion may change after use (e.g., perceived usefulness may increase or decrease) or it may be maintained 1 .

In the physical activity domain, [START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF] have shown that intention to involve in a VR-based training program may be partly determined by initial opinions towards the technology itself, before a first use. If initial perceived usefulness, perceived ease of use, perceived enjoyment, and social norms are low, the involvement in the VR-based training program is also likely to be low. Therefore, investigating, before a first use, the acceptance by athletes of a VR-HMD intended to increase their sport performance would make it possible to identify certain psychological determinants that could positively or negatively predict their intention to use this technological device that 1 A reduced number of studies distinguish acceptability (i.e., before a first use) and acceptance (i.e., after use) of a technology. But the general term "acceptance" is by far the highest ranking used in the TAM literature whatever the temporality (before/after). As a result, only the term "acceptance" is used throughout the article (although the present study focused on the perception of a technology before its first use) to be in line with the wording usually found in the literature focusing on technology acceptance before and/or after use.

they have not yet experienced. However, the TAM has not yet been validated with VR-HMD designed to enhance sport performance, neither before a first use of this device, nor after use.

Please insert Figure 1 The TAM is used extensively in many contexts in which technology may have an influence, such as healthcare, finance, gaming, and education [START_REF] Rivera | Mobile application for the timeshare industry: The influence of technology experience, usefulness, and attitude on behavioral intentions[END_REF]. This model has also been applied to athletes' acceptance of sport technologies in different domains, for instance running on a social exercise platform [START_REF] Tsai | Running on a social exercise platform: Applying self-determination theory to increase motivation to participate in a sporting event[END_REF], exergames for older adults [START_REF] Nawaz | Usability and acceptability of balance exergames in older adults: A scoping review[END_REF], sports wearable technology [START_REF] Kim | Consumer acceptance of sports wearable technology: The role of technology readiness[END_REF], fitness Apps [START_REF] Beldad | Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users' willingness to continue using a fitness app: A structural equation modeling approach[END_REF], self-report monitoring [START_REF] Rönnby | mHealth self-report monitoring in competitive middle-and long-distance runners: qualitative study of long-term use intentions using the technology acceptance model[END_REF], and sport products [START_REF] Song | Understanding users' continuance intentions to use smart-connected sports products[END_REF]. A recent review [START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF] focusing on acceptance of fitness and physical activity apps showed that the TAM was the most widely used model. But, surprisingly, studies validating the TAM with a VR-HMD designed to increase sport performance had not previously been conducted, while non-acceptance of VR by athletes was considered a threat to the use of this type of device [START_REF] Düking | The potential usefulness of virtual reality systems for athletes: a short SWOT analysis[END_REF].

Acceptance of VR-HMD in the Sport Context

The issue of acceptance of the VR-HMD in the sport context has been addressed in a reduced number of studies (e.g., [START_REF] Gradl | Virtual and augmented reality in sports: An overview and acceptance study[END_REF] for a review in cycling, see [START_REF] Mahalil | A literature review on the usage of Technology Acceptance Model for analysing a virtual reality's cycling sport applications with enhanced realism fidelity[END_REF], mainly through the ad hoc use of some of the TAM variables, notably perceived usefulness and perceived ease of use. However, these variables were used in isolation and the relationships between the different variables of the TAM have never been investigated. Thus, to date, the model itself has not been validated in the context of sport performance. The only studies using an acceptance model of VR-HMD in the sport context have examined the potential role of VR-HMD for enhancing the immersive viewer experience, for instance when watching a football match [START_REF] Kunz | Sport content and virtual reality technology acceptance[END_REF][START_REF] Rynarzewska | Virtual reality: a new channel in sport consumption[END_REF]. However, studies have already been conducted with acceptance models of the VR-HMD in different domains, such as fall prevention for older adults [START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF], business [START_REF] Manis | The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware[END_REF], and aeronautics [START_REF] Sagnier | User acceptance of virtual reality: an extended technology acceptance model[END_REF]. But despite the growing literature investigating the influence of VR on sport performance [START_REF] Düking | The potential usefulness of virtual reality systems for athletes: a short SWOT analysis[END_REF][START_REF] Faure | Virtual reality to assess and train team ball sports performance: A scoping review[END_REF][START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF][START_REF] Stone | Effectiveness and efficiency of virtual reality designs to enhance athlete development: an ecological dynamics perspective[END_REF], the issue of acceptance of VR is barely sketched and is often presented as a given: VR is assumed to be necessarily accepted by athletes because it is intended to improve their performance.

However, all the research on technology acceptance has shown that the process is not so automatic, whether in studies examining technology acceptance in general [START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF][START_REF] Venkatesh | A theoretical extension of the technology acceptance model: Four longitudinal field studies[END_REF] or VR-HMD acceptance more specifically [START_REF] Manis | The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware[END_REF][START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF]. If the VR-HMD intended to increase sport performance is not accepted by athletes, it may simply not be used or at least not be optimally used despite its initial interests related to sport performance. Some athletes may find the VR-HMD of little use because it is too disconnected from the reality and demands of their sport, while others may feel that they would not be able to operate the VR-HMD or that they would not enjoy the device. Others may feel that those around them would not encourage them to use this type of technology, especially their coach, who may find this type of technology useless or who may be unfamiliar with the use of technology in his/her training programs. All these observations may decrease the likelihood that athletes will finally use the VR-HMD and benefit from all the validated advantages of this device. Consequently, understanding acceptance before a first use of a VR-HMD intended to enhance sport performance seems crucial to identify if any initial blockages occur before use and to examine the potential predictive role of perceived usefulness, perceived ease of use, perceived enjoyment, and subjective norms on intention to use the VR-HMD. This is the first aim of the present study.

Research focusing on the role of VR in improving sport performance has been conducted with athletes of different levels of expertise, such as football players from novice to professional levels [START_REF] Wood | Testing the construct validity of a soccer-specific virtual reality simulator using novice, academy, and professional soccer players[END_REF], players of competitive high-school baseball [START_REF] Gray | Transfer of training from virtual to real baseball batting[END_REF], or beginners in table tennis [START_REF] Michalski | Getting your game on: Using virtual reality to improve real table tennis skills[END_REF]. These studies allowed the identification of skill-specific perceptual-motor mechanisms. For instance, skilled tennis players and novices have been shown to use different visual cues from the opponent to produce anticipatory judgments [START_REF] Fukuhara | The role of proximal body information on anticipatory judgment in tennis using graphical information richness[END_REF] and professional rugby players have been shown to outperform low-level players in a decision-making 3 vs. 3 situation (Correia, Araujo, Cummins, & Craig, 2012) and in an uncoupled or coupled perceptual-motor task [START_REF] Brault | Detecting deception in movement: the case of the side-step in rugby[END_REF].

Since differences in perceptual-motor skills exist in VR as a function of sport level, it is legitimate to ask whether differences in VR acceptance also exist: While elite athletes and high-level athletes are constantly looking for ways to improve their performance, should we expect that the higher the sport level, the higher the acceptance of the VR-HMD? Moreover, the effectiveness of VR has been validated in sports in which the physiological dimension is preponderant, such as running or cycling [START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF], in some tasks of team ball sports (for a review, see [START_REF] Faure | Virtual reality to assess and train team ball sports performance: A scoping review[END_REF]), in individual sports (e.g., table tennis, Michalski et al., 2019b), and in specific sport tasks (e.g., baseball batting, [START_REF] Gray | Transfer of training from virtual to real baseball batting[END_REF]. But using a VR-HMD may be considered by some athletes totally inapplicable to their own sport [START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF]. Even if the effectiveness of a technological device has been objectively validated (such as the effectiveness of the VR-HMD to improve sport performance), an athlete who believes that it is not suitable for his or her sport will not necessarily intend to use it. This process of non-acceptance is well known in the literature, for example among teachers who do not want to use a new technology in their courses that is objectively useful while they have not even tried it yet [START_REF] Scherer | The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education[END_REF]. The process is similar when elderly people find, before a first use, a technology too difficult to use while this technology has been specifically designed to be used easily by the elderly [START_REF] Chen | Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM)[END_REF]. Consequently, the second aim of the present study is to examine if differences in perceived usefulness, perceived ease of use, perceived enjoyment, subjective norms, and intention to use the VR-HMD appeared according to the sport level and the type of sport practiced in competition.

Hypotheses

We first hypothesize that intention to use the VR-HMD designed to increase sport performance would be positively predicted by perceived usefulness (H1), perceived enjoyment (H2), perceived ease of use (H3), and subjective norms (H4). Based on the TAM theoretical framework validated in other domains (e.g., education, [START_REF] Scherer | The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education[END_REF], in VR (e.g., Syed-Abdul et al., 2019), and in sport technologies other than VR-HMD (e.g., [START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF], the higher an athlete would consider the VR-HMD useful, easy to use, and encouraged to be used by those around him/her, the higher his/her intention to use it. We also hypothesize that perceived usefulness would be positively predicted by perceived enjoyment (H5) and perceived ease of use (H6), and that perceived enjoyment would be positively predicted by perceived ease of use (H7), because an athlete may find a technological device more useful if he/she considers it enjoyable and easy to use [START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF] and because a technological device that is easy to use provides more pleasure and less frustrations (van der Heiden, 2004). Finally, we expect that subjective norms would be a positive predictor of perceived usefulness (H8), perceived enjoyment (H9), and perceived ease of use (H10). Being encouraged by those around you to use a technological device can lead you to find it (a) more useful, because you trust them, (b) easier to use, because you think that those around you will be able to help, and (c) more pleasant, because you think that you will be able to share this experience with them, all of these reasons ultimately increase intention to use technology [START_REF] Al-Rahmi | Digital communication: Information and communication technology (ICT) usage for education sustainability[END_REF][START_REF] Schepers | A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects[END_REF][START_REF] Zhou | Difference between leisure and work contexts: The roles of perceived enjoyment and perceived usefulness in predicting mobile video calling use acceptance[END_REF]. Figure 1 represents the hypothesized model. We also hypothesize that the higher the sport level, the higher the scores on the five variables of the TAM, because elite and high-level athletes are constantly looking for ways to improve their performance. Regarding the influence of the sport practiced on VR-HMD acceptance, we do not provide any specific hypothesis because of the lack of support in the literature and the exploratory nature of this part of the present study.

Methods

Participants and Procedure

The study sample included 1162 French athletes (472 women, 690 men, Mage = 24.50 ± 8.51 years) who voluntarily and anonymously participated in the present study. Two inclusion criteria had to be met to participate in the study: to be at least 18 years old (legal age in France) and to usually practice a sport in competition (regardless of type of sport and level of competition). Only competitive athletes participated in the study because the VR-HMD was specifically intended to enhance sport performance. Hours of training per week were collected for all participants and the usual French classification was used to categorize their self-reported levels of competition in usual circumstances (i.e., outside the Covid-19 pandemic period): recreational level (75 participants, 5.85 ± 4.04 hours), departmental level (207 participants, 4.83 ± 2.19 hours), regional level (448 participants, 6.42 ± 2.98 hours), national level (349 participants, 8.80 ± 4.30 hours), and international level (83 participants, 14.42 ± 7.56 hours). Recreational level athletes participated very occasionally in official competitions (e.g., a running race, a football tournament) and they do not follow a regular championship like the participants of another level of expertise. A variety of sports is present among the participants. All the descriptive statistics about sports practiced and sport levels are presented in Supplementary Material 1. Most participants had never used a VR-HMD before (57.49%), many others had used it between one and three times in their entire life (39.41%), while a small minority have used it more regularly (3.10%), but never with applications designed to improve sport performance.

A nonprobability snowball sampling [START_REF] Kosinski | Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines[END_REF] was used to disseminate the online questionnaire through social networks (e.g., Facebook, LinkedIn), sport clubs, and University sport departments. Following the procedure usually conducted in the technology acceptance literature (e.g., [START_REF] Li | Health monitoring through wearable technologies for older adults: Smart wearables acceptance model[END_REF], participants had to read a short text before completing the questionnaire below. The text described what a VR-HMD is, how it could be used in sport, and its interests in improving sport performance (the full text is presented in Supplementary Material 2). This kind of procedure is mandatory in studies investigating acceptance of a technology before a first use. Participation was strictly anonymous, and respondents gave their informed consent electronically. The National Ethics Committee for Research in Sports Sciences (CERSTAPS IRB00012476-2021-16-04-103) approved the study.

Measures

Participants responded to the four items assessing perceived usefulness (e.g., "I think this VR-HMD would be useful to improve my sport performance"), the three items assessing perceived ease of use (e.g., "I think the use of this VR-HMD would be simple"), the three items assessing perceived enjoyment (e.g., "Using this VR-HMD would be fun"), the three items assessing subjective norms (e.g., "The people who are important to me would encourage me to use this VR-HMD"), and the three items assessing intention to use (e.g., "Assuming I had access to this VR-HMD, I would like to use it.") on a 1 (strongly disagree) to 5 (strongly agree) Likert scale. All the items were based on studies assessing acceptance of VR-HMDs in other domains such as business [START_REF] Manis | The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware[END_REF] and health [START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF], but items assessing perceived usefulness were adapted to the sport domain by replacing the end of each item with "…to improve my sport performance". McDonald's omegas [START_REF] Dunn | From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation[END_REF] were used to measure internal consistency, which was satisfactory for each subscale (.799 < W <.949). Descriptive statistics and McDonald's omegas for each variable are provided in Table 1. Demographic variables usually used in the TAM literature were also self-reported: gender, age, and frequency of VR-HMD use (from never to several times a week on a six-point scale). Frequency of VR-HMD use focused on the participants' prior use of a VR-HMD, but for a purpose other than improving sport performance, such as playing video games. Finally, participants were told to indicate their sport practiced in competition and their sport level (recreational, departmental, regional, national, international).

Please insert Table 1

Data Analyses

Level of significance was defined at p < .05 for all the data analyses, which were conducted using the JASP software (version 0.14.1). First, preliminary analyses were conducted: (a) the dataset was screened for missing values, (b) Mahalanobis distance (χ 2 (9) = 27.88, p < .001) at the multivariate level was used to detect gross outliers (In'nami & Koizumi, 2013), and (c) univariate normality was checked with values ≥ |2| for skewness and ≥ |7| for kurtosis indicating variables non-normal in distribution [START_REF] Curran | The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis[END_REF].

Secondly, the model's fit was evaluated through several indices [START_REF] Byrne | Structural equation modeling with AMOS: Basic concepts, applications, and programming[END_REF][START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF]: χ 2 /df ratio (value ≤ 3), the comparative fit index (CFI, value ≥ .95), the Tucker-Lewis Index (TLI, value ≥ .95), the root mean square error of approximation (RMSEA, value ≤ .05), and the standardized root mean square residual (SRMR, value ≤ .08).

A structural equation modeling (SEM) analysis based on the maximum likelihood estimations was then conducted to evaluate the hypothesized model (Figure 1). Control variables (gender, age, frequency of use, sport level) were first entered in the model to examine their potential predictive role on the main variables of the tested model. If a control variable was not found to be a significant predictor of one of the TAM variables, it was removed from the analysis for the sake of parsimony [START_REF] Zigarmi | Work locus of control, motivational regulation, employee work passion, and work intentions: An empirical investigation of an appraisal model[END_REF].

Thirdly, five one-sample t-tests (one per sport level) were used to examine potential differences between the scores of each variable of the TAM and the theoretical mean of the scales (the mean value was 3 because a five-point Likert scale ranging from 1 to 5 was used in the present study). For example, these analyses determined whether participants initially considered the VR-HMD significantly more or less useful than the mean of the scale. Because a high risk of Type I errors needs to be considered in relation to the multiple testing procedure, the Holm-Bonferroni correction was used to judge final significance [START_REF] Holm | A simple sequentially rejective multiple test procedure[END_REF]).

Effect sizes were calculated using Cohen's d. Then, five one-way ANOVAs with the factor Sport level (recreational, departmental, regional, national, international) were conducted on the scores of each variable of the TAM to determine whether significant differences occurred according to sport level. If so, differences were examined post-hoc with Tukey tests. Partial eta-squared (ηp²) was used to calculate effect sizes.

Finally, the same analyses were conducted according to the sport practiced. Only sports that were rated by more than 20 participants were included in these statistical analyses, resulting in the inclusion of seventeen sports.

The final sample size was large (N = 1162) for several reasons: (a) SEM analyses usually required large sample sizes, at least 300 participants [START_REF] Tabachnick | Using multivariate statistics[END_REF] the present study planned to collect responses from participants from different sports and different levels of competition to conduct inter-sport and inter-level comparisons, and (c) the data collection method based on nonprobability snowball sampling led to collecting the maximum amount of data over a defined period of time, without knowing in advance the final number of participants [START_REF] Kosinski | Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines[END_REF].

Results

Preliminary Results

No missing values were found because responding to each item was mandatory when completing the online questionnaire. Six participants were initially identified as outliers using the Mahalanobis distance and were excluded from the statistical analyses. The values of skewness (max = |1.054|) and kurtosis (max = |1.111|) indicated that the distribution was approximately normal. The values of skewness and kurtosis for each variable are presented in Table 1.

Validation of the Technology Acceptance Model

Two control variables (gender and age) had no significant relationships with any variables of the tested model; frequency of VR-HMD use had significant relationships with perceived ease of use only; and sport level had significant relationships with subjective norms only. The fit statistics met the criteria for a good fitting model: χ²(7, N = 1162) = 7.56, p = .373, χ 2 /df = 1.08, CFI = 1, IFI = .999, SRMR = .016, RMSEA = .008 (90% CI = .000-.038).

The results of the SEM analysis highlighted that: (a) intention to use was positively predicted by perceived usefulness (H1 supported), perceived enjoyment (H2 supported), perceived ease of use (H3 supported), and subjective norms (H4 supported); (b) perceived usefulness and perceived enjoyment were the strongest predictors of intention to use the VR-HMD; (c) subjective norms positively predicted perceived usefulness (H8 supported), perceived enjoyment (H9 supported), and perceived ease of use (H10 supported); (d) perceived usefulness was positively predicted by perceived enjoyment (H5 supported), but not by perceived ease of use (H6 not supported), which positively predicted perceived enjoyment only (H7 supported); and (e) among control variables, sport level positively predicted subjective norms, and frequency of VR-HMD use positively predicted perceived ease of use.

All the results were significant at p < .001 level. All standardized path coefficients are presented in Figure 2. In sum, the results of the SEM analysis validated the suitability of the TAM for investigating the acceptance by athletes of a VR-HMD designed to increase their sport performance.

Please insert Figure 2

Influence of Sport Level

First, the results of the one-sample t-tests showed that (a) perceived usefulness was significantly higher (ps < .001) than the mean of the scale (3) for departmental, regional, national, and international athletes, but not for recreational athletes (p = .240); (b) perceived ease of use and perceived enjoyment were significantly higher (ps < .001) than the mean of the scale for all athletes regardless of their sport level: (c) subjective norms were significantly lower (ps < .001) than the mean of the scale for recreational, departmental, regional, and national athletes, but not for international athletes (p = .974); and (d) intention to use was significantly higher than the mean of the scale for recreational (p = .003), departmental, regional, national, and international athletes (ps < .001). The detailed results of these analyses are presented in Supplementary Material 3.

Secondly, the results of the one-way ANOVAs showed that no significant effect of sport level was found on perceived usefulness, perceived ease of use, perceived enjoyment, and intention to use (ps > .05). However, a significant effect was found for sport level on subjective norms (F(4, 1157) = 4.298, p = .002, η 2 = 0.015). Post-hoc Tukey tests showed that (a) subjective norms were significantly higher for international athletes than for recreational (p < .001) and departmental (p = .046) athletes; and (b) subjective norms were significantly higher for national athletes than for recreational (p = .047) athletes. Our hypothesis was supported for subjective norms only. Means and standard deviations are presented in Supplementary Material 1. The figures for perceived ease of use, perceived enjoyment, subjective norms, and intention to use are presented in Supplementary Material 4. The results for perceived usefulness according to the sport level are presented in Figure 3.

Please insert Figure 3

Influence of Sport

First, the results of the one-sample t-tests showed that (a) perceived usefulness was significantly higher than the mean of the scale for the following sports: badminton, basketball, football, handball, rugby, tennis, and volleyball, (b) perceived ease of use and perceived enjoyment were significantly higher than the mean of the scale for all the seventeen tested sports, except perceived ease of use fo judo, (c) subjective norms were significantly lower than the mean of the scale for the following sports: athletics, badminton, basketball, cycling, football, handball, and triathlon, and (d) intention to use was significantly higher than the mean of the scale for all the tested sports, expect for cycling, swimming, riding, table tennis, and triathlon (ps >.05). The descriptive statistics and the detailed results of the t-tests are provided in Supplementary Material 3.

Secondly, the results of a first one-way ANOVA showed a significant effect of sport on perceived usefulness (F(16, 991) = 2.946, p < .001, η 2 = 0.045). Post-hoc Tukey tests revealed that triathletes had significantly lower perceived usefulness than handball (p = .006), basketball (p = .007), rugby (p = .013), football (p = .020), and badminton (p = .032) players.

While significant effects of sport were found on perceived ease of use (F(16, 991) = 1.711, p =.039, η 2 = 0.027), on perceived enjoyment (F(16, 991) = 1.751, p =.033, η 2 = 0.027), and on intention to use (F(16, 991) = 2.042, p =.009, η 2 = 0.032), post-hoc Tukey tests did not show any differences between specific sports. Finally, no significant effect of sport on subjective norms was identified (p = .067). Figure 4 represents the results for perceived usefulness of the VR-HMD depending on sport. The figures for perceived ease of use, perceived enjoyment, subjective norms, and intention to use are presented in Supplementary Materials 5, 6, 7, and 8, respectively.

Please insert Figure 4

Discussion

The aims of the present study were to investigate the suitability of the TAM to explain acceptance by athletes of a VR-HMD intended to increase sport performance and to examine the potential influence of sport level and the type of sport practiced on each variable of the TAM.

First, the results showed that the TAM was validated with the VR-HMD in the sport performance context. Before a first use, athletes' intention to use this device was positively predicted by perceived usefulness, perceived ease of use, perceived enjoyment, and subjective norms. These results were in line with the TAM studies focusing on acceptance of technology in general (e.g., [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF][START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF][START_REF] Venkatesh | A theoretical extension of the technology acceptance model: Four longitudinal field studies[END_REF], of VR-HMD (e.g., [START_REF] Manis | The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware[END_REF][START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF], and of other sport technologies (e.g., [START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF][START_REF] Kim | Consumer acceptance of sports wearable technology: The role of technology readiness[END_REF]. The fact that perceived ease of use did not predict perceived usefulness (H6 not supported) is quite frequently encountered in studies using the TAM [START_REF] Hanham | The influence of technology acceptance, academic self-efficacy, and gender on academic achievement through online tutoring[END_REF][START_REF] Sagnier | User acceptance of virtual reality: an extended technology acceptance model[END_REF] and therefore does not call into question the validity of the TAM in the present study. The VR-HMD may be considered easy to use by some athletes, but neither useful nor useless to enhance their performance, explaining that easy to use did not predict perceived usefulness in the present study. Furthermore, perceived usefulness and perceived enjoyment were the strongest predictors of intention to use this VR-HMD to enhance sport performance. Perceived usefulness is the usual strongest predictor of intention to use other sport technologies [START_REF] Angosto | The intention to use fitness and physical activity apps: a systematic review[END_REF] and the usual strongest predictor in the TAM theoretical framework [START_REF] Davis | Extrinsic and intrinsic motivation to use computers in the workplace[END_REF]) because perceived usefulness is preponderant for explaining acceptance of utilitarian technologies (van der Heiden, 2004). The VR-HMD examined in the present study may be considered by athletes a utilitarian technology since it is intended to improve sport performance. Moreover, perceived enjoyment was a strong predictor of intention to use because technologies using virtual environments are often hedonic technologies [START_REF] Sun | The input-interface of Webcam applied in 3D virtual reality systems[END_REF]. In some studies focusing specifically on VR-HMD acceptance (e.g., [START_REF] Manis | The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware[END_REF][START_REF] Mascret | Acceptance of a virtual reality headset designed for fall prevention in older adults: questionnaire study[END_REF], perceived enjoyment was even the strongest predictor of intention to use this device. Finally, the results also highlighted that subjective norms were positive predictors of all the other variables of the TAM. The more people around the athletes would encourage them to use the VR-HMD, the more they would find it useful, easy to use, pleasant, and the more they would intend to use it. This was not surprising because athletes may be influenced by their coaches, teammates, family, and peers in the sport context [START_REF] Donohue | A standardized method of assessing sport specific problems in the relationships of athletes with their coaches, teammates, family, and peers[END_REF] and the influence of subjective norms has also been shown in many studies investigating technology acceptance (e.g., [START_REF] Al-Rahmi | Digital communication: Information and communication technology (ICT) usage for education sustainability[END_REF][START_REF] Schepers | A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects[END_REF][START_REF] Zhou | Difference between leisure and work contexts: The roles of perceived enjoyment and perceived usefulness in predicting mobile video calling use acceptance[END_REF].

Secondly, the results of the present study showed that athletes of all levels had a significant intention to use the VR-HMD designed to increase their sport performance. They all initially considered it quite useful (except for recreational athletes), quite easy to use, and quite pleasant to use. Contrary to expectations, no significant differences between sport levels were found for the previous variables. These results may be explained by several reasons: (a) participants were all competitive athletes who want to increase their performances, which is precisely the stated objective of using this VR-HMD, (b) VR is very often considered a hedonic technology (van der Heiden, 2004), and (c) the average age of the participants in the present study is relatively young, so they may be more accustomed to using technology regularly. Because recreational athletes may be competing for reasons other than performance enhancement (e.g., being with friends, [START_REF] Luiggi | Development and initial validation of Sport Experiences Questionnaire (SEQ)[END_REF], they initially considered the VR-HMD not necessarily useful, although they would still want to use it if they had the opportunity. However, recreational, departmental, regional, and national athletes thought that people around them would not encourage them to use it, which was not the case for international athletes, who think that the people around them will neither support nor oppose their use of this VR-HMD. This result is challenging because it highlights a potential discrepancy between the athletes' intention to use the VR-HMD to enhance their performances and the opinion of those around them who would not necessarily advise them to do so. However, if their coach does not wish to use a VR-HMD in his/her training program, the athletes will certainly not be able to benefit from all its advantages. This could be problematic, especially for elite-level athletes for whom a continuous search for the most innovative ways to improve their performance is fundamental [START_REF] Nash | Excellence in coaching: The art and skill of elite practitioners[END_REF], especially since our results showed that international level athletes were more sensitive to the influence of their entourage than lower-level athletes.

Finally, the results showed that all the participants initially considered the VR-HMD easy and pleasant to use whatever the sport practiced, which was not surprising because ease of use and perceived enjoyment are not directly linked to the specificities of the sport practiced, but rather to the technology itself. More interestingly, the results also showed that participants of some specific sports did not find the VR-HMD significantly useful and did not have significant intention to use it to increase their performance. Some participants (e.g., cyclists, swimmers, and triathletes) may consider the VR-HMD totally inapplicable to their own sport [START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF], and therefore did not necessarily intend to use it (without rejecting it). Participants from other sports (e.g., athletics, boxing, gymnastics) did not necessarily find the VR-HMD useful (but not useless), perhaps because the perceived usefulness in the present study focused on improving sport performance in general, and these athletes could not identify precisely in their own sport how useful the VR-HMD could be in improving their performance more specifically.

The present study had some limitations that may be addressed in future research. First, the wording of the items measuring subjective norms did not make it possible to determine to what extent it was the coach or other people around the athletes who had an influence on the acceptance of the VR-HMD. Because we postulate that coaches play a crucial role, conducting a study with an item wording focusing on the influence of the coach could be relevant to (in)validate this hypothesis. Moreover, investigating acceptance of the VR-HMD not by the athletes themselves but by the coaches may also be a promising perspective for a future study [START_REF] Greenhough | Perceptions of professional soccer coaches, support staff and players toward virtual reality and the factors that modify their intention to use it[END_REF]. Secondly, it was impossible in the present study to investigate the interaction between sport level and sport practiced due to insufficient numbers of participants in each of the categories that would have been created.

Thirdly, the text that was read before completing the questionnaire described what a VR-HMD is, how it could be used in sport, and its interests in improving sport performance (see Supplementary Material 2). This text was not intended to be exhaustive regarding all possible applications of VR to improve sport performance, but other potential applications could have been mentioned (e.g., helping athletes familiarize themselves with new environments, mental training, maintaining training during an injury). This might have led to greater usefulness / intention to use scores, particularly for athletes from repetitive/motoric sports (e.g., cycling).

Fourthly, while the present study has provided interesting results to better understand acceptance of the VR-HMD before first use, the TAM literature showed that acceptance of technology may increase or decrease after first use and/or after regular use [START_REF] Venkatesh | Technology acceptance model 3 and a research agenda on interventions[END_REF][START_REF] Venkatesh | A theoretical extension of the technology acceptance model: Four longitudinal field studies[END_REF]. Based on a pre-and post-test design, it would be interesting to compare acceptance by athletes of the VR-HMD before and after a first use.

However, this perspective requires the implementation of virtual environments specific to each sport to develop sports skills that are also specific. Fifthly, the nonprobability snowball sampling used in the present study led to categories of different competitive levels involving different numbers of participants. Future studies may recruit equal numbers of participants for each level. Finally, a recent study [START_REF] Sagnier | User acceptance of virtual reality: an extended technology acceptance model[END_REF] showed that cybersickness was a negative predictor of intention to use a VR-HMD when performing an aeronautical assembly task in VR. It would be relevant to investigate if the pattern would be similar or specific for athletes after a first use of a VR-HMD intended to enhance sport performance.

Conclusion

The present study showed that a VR-HMD intended to improve sport performance is mostly well accepted by athletes of different sport levels before a first use, even if differences appeared in some specific sports. Identifying acceptance by athletes of such a device may contribute to increase the likelihood that it will be used by athletes of different levels and from different sports, through a better understanding of the variables that can affect the intention to use it, namely perceived usefulness, perceived ease of use, perceived enjoyment, and subjective norms. Even if the effectiveness of VR on sport performance has been validated and studies continue to improve it [START_REF] Düking | The potential usefulness of virtual reality systems for athletes: a short SWOT analysis[END_REF]Michalski et al., 2019a;[START_REF] Neumann | A systematic review of the application of interactive virtual reality to sport[END_REF], the question of the acceptance of the VR-HMD deserves to be systematically asked with this type of device to allow athletes to benefit from its full potential, especially high-level athletes whose demands during training are considerable. The Technology Acceptance Model (TAM) tested in the present study. Notes. PU = Perceived Usefulness, PEOU = Perceived Ease of Use, PE = Perceived Enjoyment, SN = Subjective Norms, ITU = Intention to Use, M = Mean, SD = Standard deviation

Figure 2

 2 Figure 2Validated structural model.

Figure 3

 3 Figure 3Perceived usefulness according to sport level

Figure 4

 4 Figure 4Perceived usefulness according to sport.

Table 1

 1 Descriptive statistics, skewness, kurtosis, and internal consistency.

		Perceived	Perceived	Perceived	Subjective	Intention
		usefulness	ease of use	enjoyment	norms	to use
	Mean	3.395	3.763	4.088	2.658	3.753
	Standard deviation	1.063	0.838	0.796	1.057	1.141
	Skewness	-0.368	-0.581	-1.054	0.289	-0.789
	Kurtosis	-0.560	0.110	1.111	-0.436	-0.284
	McDonald's omega	.949	.807	.799	.939	.945

  Descriptive statistics by sport and by sport level. Descriptive statistics by sport and by sport level.

	Supplementary Material 1 (Part 2). Recreational Departmental	Regional	National	International	Total	PU PU		PEOU PEOU	PE PE		SN SN		ITU ITU
	Padel		Recreational Departmental 0 0	Regional 1	National 1	International 0	Total 2	M 3.00	SD 1.41	M 3.00	SD 1.41	M 3.83	SD 1.65	M 3.17	SD 2.12	M 4.83	SD 0.24
	Aerobatics Pétanque		0 0	0 0	0 0	0 1	2 0	2 1	4.63 5.00	0.53 -	4.17 4.00	0.71 -	4.33 5.00	0.94 -	4.00 4.33	1.41 -	4.83 3.67	0.24 -
	American football Rhythmic gymnastics	0 0	0 0	1 1	2 1	0 1	3 3	3.67 2.08	0.38 1.46	4.11 2.44	0.51 0.51	4.00 3.44	0.67 1.68	2.22 2.33	1.02 0.88	3.00 3.44	1.76 1.58
	Archery Riding		0 4	0 4	1 10	0 8	1 1	2 27	3.13 3.33	2.30 1.24	2.83 4.10	0.24 0.75	3.83 4.19	1.18 0.78	3.00 2.90	0.00 1.36	4.83 3.94	0.24 0.98
	Athletics Roller hockey		8 0	9 0	74 0	50 4	3 0	144 4	3.14 3.81	1.07 0.99	3.72 4.67	0.84 0.67	4.00 4.50	0.79 0.58	2.52 2.75	1.08 0.50	3.82 2.92	1.08 1.73
	Badminton Rowing		2 0	20 0	12 0	13 3	4 2	51 5	3.60 3.25	0.90 1.26	3.90 3.00	0.73 0.94	4.12 3.73	0.68 1.19	2.56 2.33	0.88 1.22	3.78 4.07	0.99 0.89
	Baseball / Softball Rugby		0 4	0 4	0 29	1 27	0 3	1 67	1.00 3.62	-0.91	2.33 3.74	-0.84	3.33 4.06	-0.86	1.00 2.75	-1.11	1.00 3.84	-1.30
	Basketball Sailboat		1 0	28 0	48 0	11 1	0 0	88 1	3.61 5.00	0.97 -	3.97 4.00	0.79 -	4.34 4.33	0.61 -	2.61 1.33	1.12 -	3.89 4.67	1.13 -
	Beach volley Sailing		0 0	0 0	1 0	0 2	0 6	1 8	2.00 3.84	-0.78	4.00 3.92	-0.79	3.67 4.42	-	1.00 3.08	-1.14	3.00 4.04	-0.60
	Biathlon Shooting sports		0 0	0 0	0 0	0 1	1 0	1 1	3.50 4.00	--	3.33 2.00	--	4.67 3.33	--	3.00 2.67	--	2.67 1.67	--
	Boxing Skipping rope		5 0	3 0	6 0	12 0	4 1	30 1	3.43 3.75	1.15 -	3.73 3.33	1.09 -	4.04 4.00	0.89 -	2.62 2.00	1.07 -	3.12 4.00	1.34 -
	Canoeing Snowboard		0 1	0 0	0 0	1 0	4 0	5 1	3.30 3.50	1.08 -	3.53 2.00	0.45 -	4.00 3.00	1.00 -	2.33 2.67	1.18 -	4.07 4.00	0.72 -
	Climbing Squash		2 0	3 0	3 2	1 0	2 0	11 2	2.95 3.13	0.98 0.18	3.45 4.17	1.11 0.24	4.00 4.17	0.80 0.24	2.58 1.50	0.73 0.71	3.97 3.33	0.86 2.36
	Cross-country skiing Street workout	0 1	0 0	1 1	1 0	0 0	2 2	2.75 3.63	0.00 0.53	4.33 4.50	0.47 0.71	4.50 4.83	0.71 0.24	2.67 2.33	0.94 0.47	5.00 4.33	0.00 0.94
	CrossFit Surf		0 0	1 1	3 1	1 0	0 0	5 2	3.35 2.75	1.54 1.06	3.80 3.83	1.39 1.65	4.67 2.50	0.33 1.18	3.00 2.17	1.22 1.65	4.13 3.50	1.32 2.12
	Curling Swimming		0 1	0 2	0 17	0 10	1 0	1 30	3.75 3.00	-1.32	3.00 3.59	-0.94	3.00 3.82	-0.99	3.00 2.46	-1.23	4.00 3.82	-1.14
	Cycling Table tennis		1 0	3 8	6 12	9 6	5 0	24 26	3.16 3.31	1.14 0.94	3.90 3.85	0.76 0.78	4.13 3.83	0.91 0.76	2.18 2.98	0.91 0.97	3.72 3.64	1.07 1.17
	Dance Tennis		2 6	1 21	1 34	4 6	2 2	10 69	3.58 3.47	0.95 1.04	4.13 3.89	0.48 0.83	4.43 4.24	0.42 0.81	3.23 2.71	1.03 1.00	3.90 3.91	0.85 1.04
	Downhill skiing Trail		1 3	2 0	2 7	0 1	0 0	5 11	2.95 3.02	1.27 1.12	3.27 3.64	1.01 0.82	2.73 3.79	0.64 0.85	1.40 2.30	0.55 0.74	3.53 3.48	1.71 1.05
	Fencing Triathlon		1 11	0 2	2 14	12 10	14 3	29 40	3.50 2.81	1.28 1.05	3.79 3.47	0.88 0.87	4.22 3.86	0.91 0.83	3.20 2.35	1.21 0.95	3.43 3.77	1.00 1.30
	Figure skating Twirling stick		0 0	0 0	0 0	1 2	3 0	4 2	2.38 2.88	1.38 0.18	2.67 4.50	1.56 0.71	3.42 4.67	1.45 0.47	1.92 2.83	1.07 0.71	3.50 4.17	1.73 1.18
	Fitness Ultimate		1 1	0 0	0 2	0 2	0 0	1 5	2.00 2.75	-0.90	2.00 3.13	-1.39	2.67 3.80	-1.17	1.67 2.93	-1.59	5.00 4.53	-0.45
	Floorball Volleyball		0 2	0 8	0 17	1 17	1 0	2 44	3.88 3.45	0.18 1.01	4.50 3.83	0.71 0.89	4.17 4.03	0.24 0.86	3.67 2.69	0.94 1.07	3.50 3.47	1.18 1.18
	Football Water polo		9 0	57 0	54 0	17 2	1 0	138 2	3.51 3.88	1.09 0.18	3.71 3.83	0.75 0.24	4.05 4.83	0.77 0.24	2.71 3.17	1.00 0.24	3.77 3.00	1.10 2.83
	Freestyle skiing Weightlifting		0 1	0 1	0 1	0 1	1 0	1 4	4.50 3.50	-0.89	3.67 3.58	-0.50	4.67 3.75	-0.69	4.00 2.58	-1.20	3.33 4.08	-1.07
	Golf Windsurfing		3 0	3 0	3 0	2 0	0 1	11 1	3.95 4.25	1.05 -	4.21 3.00	0.70 -	4.27 4.00	0.68 -	2.94 4.00	1.09 -	3.39 4.33	1.48 -
	Grappling Wrestling		0 0	0 0	1 0	0 1	0 1	1 2	4.00 4.50	-0.71	5.00 3.83	-1.65	4.67 4.33	-0.94	4.00 3.17	-2.59	5.00 4.33	-0.94
	Gymnastics Total		0 75	1 207	16 448	28 348	0 84	45 1162	3.03	1.03	3.67	0.80	4.07	0.53	2.64	0.99	3.67	1.21
	Handball PU	M/SD	2 3.16/1.15	21 3.44/1.04	45 3.39/1.07	48 3.39/1.04	1 3.54/1.09	117	3.58	0.96	3.79	0.70	4.19	0.77	2.66	0.99	3.48	1.25
	Hockey PEOU	M/SD	0 3.56/1.04	0 3.77/0.78	0 3.78/0.81	1 3.78/0.84	0 3.75/0.91	1	3.75	-	3.33	-	3.67	-	3.00	-	4.00	-
	Ice hockey PE	M/SD	0 4.00/0.80	0 4.18/0.75	0 4.08/0.80	1 4.06/0.80	0 4.13/0.86	1	3.25	-	3.00	-	3.33	-	3.00	-	3.33	-
	Judo	SN	M/SD	2 2.31/1.11	2 2.62/0.94	14 2.65/1.07	14 2.68/1.06	7 3.00/1.13	39	3.37	1.06	3.49	0.99	4.07	0.75	2.71	1.08	4.23	0.77
	Lifesaving sport ITU	M/SD	0 3.45/1.26	0 3.81/1.07	0 3.78/1.17	1 3.71/1.11	0 3.94/1.11	1	3.75	-	2.33	-	4.67	-	3.00	-	3.67	-
	Martial Arts		0	1	3	5	6	15	4.18	0.83	4.04	0.69	4.24	0.80	3.07	1.16	3.98	1.19
	Motorbike		0	0	1	0	0	1	3.25	-	3.67	-	5.00	-	5.00	-	3.67	-
	Orienteering		0	1	1	4	0	6	3.25	1.05	4.22	0.54	4.61	0.65	2.72	0.77	3.67	0.99

Supplementary Material 1 (Part 1).

Funding

This work is included in the REVEA project supported by a government grant managed by the French National Research Agency (ANR) as part of the « Investissements d'Avenir » program (20-STHP-0004).

The funding source was not involved in study design, in the collection, analysis, and interpretation of data, in the writing of the article, or in the decision to submit the article for publication.

Supplementary Material 2. Text read by the participants before completing the questionnaire.

The virtual reality headset would allow you to be immersed in a virtual environment (see photos). You could then train in your favorite sport by being exposed to perfectly controlled situations. The virtual reality training modes would be adapted to the specificities of each sport, to the problems encountered, to your needs, and to your performance objectives.

You could for example: -Carry out tasks that will allow you to improve your performance in specific areas (perception, decision making, action control, reaction time, etc.), -Compete against a virtual opponent or cooperate with a virtual partner, -Benefit from real-time or delayed feedback on the relevance of your choices and actions, -Watch techniques performed by experts, controlling the viewing angle yourself and being totally immersed in the action, to improve your own technique.

Of course, training with the virtual reality headset is not intended to replace real training. In addition to your regular training, each virtual reality protocol would allow you to work on specific aspects to improve your performance in your favorite sport. Supplementary Material 3. Results of the one-sample t tests comparing scores of TAM variables with the mean of the scales.

Perceived usefulness

Perceived ease of use Notes. For the Student t-test, effect size is given by Cohen's d and the alternative hypothesis specifies that the mean is different from 3 (i.e., mean of the scale).

Supplementary Material 4. Perceived ease of use, perceived enjoyment, subjective norms, and intention to use according to sport level.