The Light and Dark Side of VR: A New Hope for Meetings—or Just More Fatigue?

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Yannick Frontzkowski, Philip Gubernator, Marvin Grabowski, Jörg Felfe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7036583/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As videoconferencing (VC) has become a pillar of modern collaboration, studies have shown the downsides of engaging in—particularly videoconference fatigue (VCF), a multidimensional construct encompassing general, emotional, motivational, social, and visual exhaustion. Immersive virtual reality (VR) platforms, which promise more natural and socially rich interactions, have been proposed as a possible solution. However, due to the novelty of this quickly evolving technology, the psychological effects of VR meetings remain underexplored. This study investigates how VR and VC meetings differentially affect VCF, and whether cognitive load and positive meeting interactions mediate these effects. We conducted a within-subject experiment (N = 84), where participants completed two 15-minute collaborative meetings—one via Microsoft Teams (VC condition) and one via Meta Quest 2 VR headsets in Horizon Workrooms (VR condition). The meetings involved a problem-solving task requiring information sharing among team members. After each meeting, participants reported levels of five fatigue dimensions, mental and physical load (as proxies for cognitive load), and the quality of positive interactions. Structural equation modeling was used to test direct and indirect effects of meeting condition on fatigue outcomes. Findings revealed a dual effect of VR: while participants reported significantly more general, emotional, and visual fatigue in VR compared to VC, they also experienced more positive social interactions. Surprisingly, mental and physical load did not mediate these effects, contradicting established theories that emphasize cognitive overload as the main driver of VCF. Instead, positive interactions partially mediated reductions in social and motivational fatigue in VR, suggesting immersive features may foster more engaging and socially satisfying communication, even as other fatigue dimensions increase. These results refine our understanding of fatigue in immersive contexts. The data suggest that cognitive load may not be the driver of the negative effects of VR meetings This challenges the dominant cognitive load perspective and highlights the importance of perceptual and affective mechanisms, and moreover points out the question: What are the negative drivers of VCF in VR? The study contributes theoretically by disentangling multiple dimensions of VCF, advancing a dual-path model of immersive meeting outcomes, and providing experimental evidence. Practically, it suggests that VR may enhance interaction quality but simultaneously increase fatigue, posing a trade-off for organizations adopting immersive tools. Careful implementation, user onboarding, ergonomic design, and task alignment will be critical for sustainable use. Future work should examine longer-term adaptation, diverse VR hardware, physiological measures of fatigue, and different task types to determine under what conditions VR meetings can offer net benefits without compromising user well-being. Figures Figure 1 Figure 2 Figure 3 Introduction Videoconferencing (VC) has become essential to modern work (Derouech et al. 2024), allowing dispersed teams to communicate across geographical boundaries. For example, Evans (2020) reported a sharp rise in Zoom usage, growing from about 10 million participants in December 2019 to over 300 million weekly users by April 2020. Likewise, a diary study by Cao et al. (2021) with Microsoft employees, found many of the employees had more meetings than before. Recently, companies have begun to experiment with immersive virtual-reality (VR) meeting platforms that extend the VC continuum by representing participants as three-dimensional avatars (Hennig-Thurau et al. 2023). Fortune 500 firms such as Accenture and PwC are already running onboarding and design-sprint sessions entirely in VR, signaling strong commercial interest in immersive meeting technology (Brown et al. 2023; Hernandez and Rivet 2024). In view of the increase and further development of these technologies, questions about the associated opportunities and risks for performance and health are becoming more important. VC tools such as Microsoft Teams or Zoom offer undeniable benefits, amongst which are reduced travel time, cost savings, and rapid collaboration. However, research has shown that repeated or prolonged use of videoconferencing can provoke adverse outcomes. In particular, a large body of research has focused on so-called “videoconference fatigue” (Fauville et al. 2021a; Fauville et al. 2021b; Bailenson 2021; Wiederhold 2020; Nesher Shoshan and Wehrt 2022; Riedl et al. 2023), formerly known as “zoom fatigue”. Videoconference fatigue (VCF) can be defined as "a feeling of exhaustion from participating in video conference calls" and may manifest in general (i.e. exhaustion), and more specific emotional, motivational, social, and visual strain (Fauville et al. 2021a). It is an open question, if further technological development, e.g. replacing VC with VR may change the risk of fatigue. Several antecedents for VCF have been identified in the VC literature. Bailenson (2021) highlights reduced non‑verbal bandwidth, constant self‑view, and perceived personal‑space invasion which hinder interaction possibilities and he potential role of cognitive load as a explaining mechanisms to VCF. Fauville et al. (2021b) also showed in an experimental study that interpreting nonverbal cues requires more cognitive load which predicts VCF. It is an open question if upcoming communication technology such as VR platforms could present an alternative that tackle these issues and reduce the risk of VCF. By providing three-dimensional immersive channels, VR has the potential to reduce certain technical limitations of classic videoconference systems. These immersive spaces could offer more possibilities for natural ways of communication and therefore reduce interaction restrictions. For example, in VR environments, participants can maintain direct eye contact in ways that reduce potential misunderstandings, which might lead to clearer social interactions. Furthermore, VR facilitates the perception of spatial relationships and directional audio cues, which could make communication easier. VR offers high levels of immersion, which could foster deeper social contact. However, such an environment could foster cognitive load because of the heightened technical hinderances. For example, reduced resolution, connectivity issues and low wearing comfort require additional cognitive capacity to compensate. Whereas fatigue is well documented for videoconferences, evidence for fatigue with immersive VR meetings is scarce and mixed. We are only aware of two experimental studies that directly compare VC and VR. Macchi and Pisapia (2024) report higher visual strain and emotional fatigue for VR, suggesting more cognitive load, but improved cooperation and openness which may be due to more positive interactions, which describes the received enjoyableness of interacting with one another. Similarly, Hennig-Thurau et al. (2023) found, that VR compared to VC increases positive interactions and social presence, while also increasing emotional fatigue. They conclude that high immersion can be a double-edged sword: while it seems to foster positive interactions due to more realism, it increases exhaustion due to higher demands. These demands include navigating virtual spaces, wearing head-mounted displays (HMD) for prolonged periods, and adapting to unfamiliar avatars and controls also suggesting more cognitive load. However, cognitive load was not assessed in both studies, which makes it unclear whether these increased mental demands with VR may translate in fatigue. Hence, current findings cannot explain why particular fatigue facets rise (visual, emotional). Moreover, the effects of VR on other facets (social, motivational, general) have not been examined yet. Guided by cognitive-load theory and social-interaction frameworks, we propose two opposing parallel mediators—(a) cognitive load and (b) quality of positive social interaction—that may explain different effects on fatigue subdimensions. As we will argue, VR is associated with higher cognitive load leading to more visual and emotional fatigue, but also associated with better social interactions leading to less social, motivational and general fatigue. The aim of the present paper is to delve into (a) how VR meetings compare to conventional videoconferences along different facets of fatigue, and (b) whether cognitive load and/or (c) positive interactions mediate these different effects. To test our hypotheses, we conducted a 2 (pre vs. post) x 2 (VC vs. VR) experimental within subject design, in which groups of three participants collaborated in a VC and a VR meeting. To make possible differences between the two media visible, intensive interaction is required in which all participants are highly involved. Therefore, a problem-solving task was chosen in which the participants had different information and goals to accomplish, unlike previous VR-meeting research that has mostly centered on creative ideation or design-sprint tasks. Our study makes several contributions. Firstly, we add to the ongoing theoretical debate of cognitive load as a mediator on fatigue and how to harness the positive aspects of virtual platforms for collaborative work while minimizing the burden of fatigue. Secondly, we expand the methodological approaches to this topic by offering between and within data. By using a within-subject and between-subjects design, we provide novel empirical insights into the specific strengths and weaknesses of immersive communication tools. Third, we respond to recent calls for further research on how and why different meeting tools can fatigue participants (REF: Thurau et al., p.14), especially because of the lack of empirical evidence of VCF in VR meetings. Fourth, we also aim to close the literature gap on what specific fatigue facets differ between the use of VC and VR. Lastly, in contrast to prior studies focusing on ideation or design tasks (Macchi and Pisapia 2024; Hennig-Thurau et al. 2023), we implement a new meeting task that emphasizes information sharing and discussion, enabling a more generalizable understanding of interaction demands. Theory Videoconference Fatigue Fatigue broadly refers to a state of reduced energy and increased subjective effort that arises after prolonged or intense task engagement (Hockey 2013). Within videoconferencing, VCF describes how individuals feel more physically and socioemotionally exhausted, less motivated, and struggle to concentrate after continuous online meetings (Bailenson 2021; Fauville et al. 2021b). VCF itself can lead to more negative work and health-related outcomes. Excessive fatigue has been linked to lower job satisfaction, decreased performance, and higher stress (Wiederhold 2020). Prolonged videoconferencing can erode psychological well-being, undermining teamwork and collaboration (Cao et al. 2021). Fatigued employees are more prone to burnout and may disengage from work responsibilities, adversely affecting both individual and organizational outcomes (Nesher Shoshan and Wehrt 2022). Fauville et al. (2021a) suggest five facets—general, motivational, social, emotional and visual fatigue—that vary in intensity depending on the stimuli meeting platforms present. For instance, when users look into a virtual reality head mounted display (HMD), they might see the pixels of the display flicker, which may heighten visual fatigue by forcing the eyes to adapt continuously. Also, the vergence–accommodation conflict inside head-mounted displays is a well-known driver of visual fatigue (Souchet et al. 2023). Several broad categories help explain the antecedents of videoconference fatigue. First, technological and environmental factors involve the platform’s design, internet connectivity, screen sizes, or camera self-view, all of which force participants to expend extra effort interpreting distorted cues (Nesher Shoshan and Wehrt 2022; Hinds 1999, 1999). However, VR’s more natural spatial cues can sometimes ease social or emotional strain compared to two-dimensional grids. Likewise, improvements in bandwidth and camera resolution have reduced latency and pixelation over time (Knoblauch 1999), yet persistent shortcomings—such as unreliable eye contact and limited spatial cues—still hamper the realism of traditional videoconferences. Second, interpersonal and social factors center on continuous on-camera exposure and perceived close-up interactions that can mimic invasions of personal space, intensifying arousal (Bailenson 2021). While typical video calls may exacerbate self-consciousness, VR’s immersive platforms might reduce that pressure by allowing more dynamic, less “forced” engagements. Third, personal and cognitive factors involve individual differences such as attention capacity, self-consciousness, and susceptibility to overstimulation. For instance, users with higher social anxiety or limited familiarity with videoconferencing tools often spend extra mental resources managing the constant stream of visual and auditory input, thereby exacerbating fatigue (Fauville et al. 2021a; Wiederhold 2020; Lim et al. 2025). These studies only glimpse into a wider field of antecedents of VCF. By highlighting the interplay among technology, social dynamics, and personal thresholds, these three categories illustrate how diverse, yet interrelated stressors amplify the experience of videoconference fatigue. Virtual Reality and Immersion Immersion in VR goes beyond merely using a head‑mounted display; it envelops users in multisensory stimuli (Slater 2018). Presence describes the subjective experience of “being there” (Slater and Wilbur 1997) whereas social presence captures the sense of being with others (Gunawardena 1995). From a psychological viewpoint, immersion can be viewed as the system’s capability to present an all-encompassing, coherent set of stimuli. At the same time, presence describes the subjective experience of “stepping into” that reality (Slater 2018). In a VR-based meeting, for example, immersion is supported by 360° head tracking, spatial audio that conveys where voices originate in the virtual space, and motion controllers that capture gestures. The user’s presence emerges when these technological features align seamlessly to create an intuitive, realistic feeling of “here and now” in a shared space. This VR-mediated sense of presence can only be achieved through the head-mounted display and is described in human-computer interaction literature as qualia (Latoschik & Winriech, 2022). Importantly, immersion has multiple layers. While sensory immersion reflects the hardware’s ability to engage users’ senses comprehensively, cognitive immersion involves mental engagement, such as when users must process realistic visual depth or track hand movements in three dimensions (Sanchez-Vives and Slater 2005). Emotional immersion emerges when users feel genuine affective responses—excitement, empathy, or stress—prompted by events in the virtual environment (Slater, 2018). In collaborative VR, emotional immersion might intensify due to avatars’ expressive gestures and the sensation of co-presence with colleagues, potentially heightening both involvement and fatigue (Hennig-Thurau et al., 2023). Yet this immersion can cut both ways. Richer, more realistic cues can ease certain communication barriers—for instance, participants can lean in to show interest or make eye contact that “feels real”—enhancing group cohesion and reducing the guesswork associated with nonverbal signals (Kock, 2004). At the same time, these cues can raise cognitive demands, particularly for first-time users who must learn new interaction paradigms like hand controllers or avatar movement (Macchi & Pisapia, 2024). If hardware or software fidelity is lacking—e.g., lag in tracking, awkward avatar faces—immersion may feel unnatural , prompting discomfort or frustration. Physical factors such as the weight of the HMD or heat buildup inside the visor can further strain users, ultimately contributing to different dimensions of fatigue, including visual and emotional overload (Bailenson 2021; Fauville et al. 2021a). In short, VR aims to reduce the artificiality of remote collaboration by leveraging immersion; however, the degree of immersion hinges on system design, user familiarity, and the realism of the presented stimuli. When well-implemented, immersive features can bring remote communication closer to face-to-face interaction, raising the sense of co-presence and fostering more genuine social interaction. However, as the studies on VCF suggest, these very features can also amplify strains—especially if the technology is novel or imperfect—underscoring the need for balanced, user-centric implementations of VR in professional settings. Strains in VR could stem from the novelty of the technology (Macchi and Pisapia 2024), causing the participant to potentially be disoriented in the virtual space and requiring extra effort to identify and navigate through menus and options. Grounded in these theoretical arguments, we propose that the immersive requirements of VR (e.g., donning an HMD, navigating 3D space) impose higher general VFC compared to VC. Thus: H1 a : VR meetings lead to more general fatigue than VC meetings. Immersive realism can heighten emotional involvement, so even minor technical glitches or self-presentation concerns in VR can feel more intense, contributing to greater emotional drain. Whereas social involvement primarily captures the sense of connectedness and group interaction, emotional involvement focuses on the intensity of personal affective responses—an aspect that can escalate more readily in highly immersive VR settings, thereby contributing to emotional fatigue. Thus: H1 b : VR meetings lead to more emotional fatigue than VC meetings. Head-mounted displays demand continuous focus on close-up screens and can introduce optical strain (Macchi and Pisapia 2024). This contrasts with VC, where conventional laptop or desktop screens may be easier on the eyes. Thus: H1 c : VR meetings lead to more visual fatigue than VC meetings. Cognitive Load Theory and Naturalness Theory Cognitive Load Theory (Sweller 1988, 2012) contends that limited working‑memory resources are taxed by complex or dense stimuli. When tasks become increasingly complex or stimuli become denser, the cognitive load on individuals rises. Within videoconferencing scenarios, prior studies consistently demonstrate that screen-mediated communication requires substantial concentration to interpret facial expressions, manage technological aspects, and remain self-aware on camera, culminating in heightened fatigue (Bailenson 2021; Fauville et al. 2021b) In VR meetings, users face novel mental and physical demands, such as operating unfamiliar three-dimensional interfaces, handling head-mounted displays, maintaining spatial orientation, and deciphering avatar movements (Hennig-Thurau et al. 2023; Macchi and Pisapia 2024). For instance, an experimental study by Narasimha et al. (2019) found that participants performing a card sorting task perceived higher mental, physical, and temporal workload, alongside elevated effort and frustration, in VR compared to face-to-face or videoconference conditions. These additional demands may intensify cognitive load, thereby exacerbating fatigue. Indeed, some users in immersive VR sessions report the need to “focus extra hard” to synchronize head and eye movements with gestural cues—an effort that can strain mental resources (Macchi and Pisapia 2024). Conversely, while VC calls may present a simpler interface, they still require attention to on-screen cues and can involve overlapping conversations, albeit with fewer immersive stimuli. For example, standard video calls often entail divided attention—particularly when multiple participants speak simultaneously—but do not necessitate wearing head-mounted equipment. Naturalness Theory (Kock 2004) posits that communication media offering a closer approximation to face-to-face interactions reduce psychological strain. Since VR often incorporates spatial audio, simulated eye contact, and full-body gestures, it has the potential to deliver more organic social cues than VC, possibly alleviating certain types of cognitive or social friction. Recent work indicates that spatial audio and precise avatar alignment can heighten social presence, streamlining turn-taking and mitigating misunderstandings (Hennig-Thurau et al. 2023; Riedl 2022). However, if immersive features are suboptimal—e.g., due to low-resolution avatars or delayed head-tracking—they may ironically become cognitively taxing and emotionally unsettling (Bailenson 2021). Thus, the very qualities intended to enhance realism can inadvertently contribute to fatigue when perceived as insufficiently “natural” (Fauville et al. 2021b; Fauville et al. 2021a). Both theories suggest that well-designed VR immersion can reduce certain burdens, such as social awkwardness or misinterpretation of nonverbal signals. Yet incomplete realism or unaccustomed hardware may amplify cognitive load, emotional reactivity, and physical unease—for instance, extended head-mounted display use can induce eye strain or cybersickness (Macchi and Pisapia 2024). Essentially, VR might ease some media-specific stressors (e.g., difficulty discerning nonverbal cues) while simultaneously adding new sources of strain (e.g., managing bulky equipment), which could accentuate fatigue—particularly among new adopters (Macchi and Pisapia 2024). Furthermore, the novelty effect of VR—where initial excitement offsets fatigue—can diminish with time, or conversely, repeated use may mitigate cognitive overhead as users become more familiar with immersive interfaces (Macchi and Pisapia 2024; Riedl et al. 2023). Emerging research on videoconference fatigue illuminates how these theories intersect. Fauville et al. (2021a), for example, report that persistent self-view in 2D meetings can elevate mental load due to increased self-awareness. Meanwhile, VR typically limits direct self-view, yet requires continuous synchronization of head movements and avatar representation, generating a distinct but comparably high cognitive strain. Moreover, the heightened sense of social presence in VR can intensify emotional involvement, thus exacerbating fatigue when technical disruptions undermine the immersive experience (Hennig-Thurau et al. 2023). These findings underscore that VR’s “naturalness” advantage often depends on technological sophistication and user adaptability. The light path of VR: Positive Interactions A growing body of research suggests that virtual reality platforms can support richer engagement and more intuitive communication compared to traditional videoconferencing (Hennig-Thurau et al. 2023; Dey et al. 2024; Grabowski et al. 2024; Latoschik and Wienrich 2022). The sense of co-presence, enabled by spatial audio and avatar-based gestures, may increase immediate feedback and nuanced nonverbal cues. This heightened interactivity fosters a stronger perception of social connection, often referred to as social presence (Gunawardena, 1995; Kang et al., 2007). In line with Naturalness Theory (Kock, 2004), these additional sensory channels and real-time cues approximate face-to-face interaction more closely, leading to a smoother flow of conversation and more comfortable group dynamics (Yoon & Leem, 2021). Moreover, immediacy—the speed and spontaneity of feedback—can be higher in VR because participants can more effortlessly observe physical orientation and proximity, even if mediated by avatars (Grabowski et al. 2024; Hennig-Thurau et al. 2023). This sense of “shared space” allows for faster and more organic turn-taking, potentially boosting positive interpersonal outcomes such as perceived friendliness, openness, or collaboration (Gunawardena, 1995; Norton, 1986). By contrast, VC’s 2D interface might limit the richness of feedback cues (e.g., reliance on small on-screen windows, less fluid eye contact), potentially leading to lower levels of positive interactivity. Thus: H2: VR leads to more positive interactions than VC. If VR indeed increases positive interactions, a subsequent question is whether this enhanced sense of engagement and connectivity offsets or mitigates certain dimensions of fatigue. According to social presence theory, heightened interactivity and immediacy can reduce feelings of social awkwardness, boost motivation, and even alleviate emotional strain (Gunawardena, 1995; Kang et al., 2007). Thus, when meetings feel more personal and smoothly interactive, participants may be less likely to experience fatigue—even if the environment is technologically demanding (Bailenson, 2021). Moreover, in line with the Media Naturalness Theory, a more natural interaction through more natural ways of moving and communicating in VR, could also foster a positive sense of interaction with one another. Positive interactions may help maintain overall energy by making tasks feel more engaging and less monotonous. Even if the medium is demanding, participants who experience a high level of interactive may remain more alert and less fatigued overall. Thus: H3 a : Positive interactions mediate the effect of VR vs. VC on general fatigue in a way, that VR leads to higher positive interactions which in turn predict less general fatigue. Enhanced social presence and immediate feedback can fuel group cohesion and enthusiasm, encouraging continued effort and reducing the motivational drop-off that often accompanies remote communication (Yoon & Leem, 2021). H3 b : Positive interactions mediate the effect of VR vs. VC on motivational fatigue in a way, that VR leads to higher positive interactions which in turn predict less motivational fatigue. When virtual environments support fluid interaction, social connection could feel more authentic and less contrived. As a result, individuals may be less drained by interpersonal demands (Fauville et al., 2021b). H3 c : Positive interactions mediate the effect of VR vs. VC on social fatigue in a way, that VR leads to higher positive interactions which in turn predict less social fatigue. High positive interactivity can reduce uncertainty, a key driver of emotional exhaustion in online communication (Nesher Shoshan & Wehrt, 2022). Timely nonverbal cues (e.g., nods, facial expressions, gestures) can convey empathy and support, thereby alleviating emotional strain. H3 d : Positive interactions mediate the effect of VR vs. VC on emotional fatigue in a way, that VR leads to higher positive interactions which in turn predict less emotional fatigue. The Dark Path of VR: Cognitive Load Despite VR’s potential for richer interactivity, it can also increase cognitive load due to the mental and physical demands of novel hardware (HMD, controllers), the need to track spatial orientation, and the relative novelty of avatar-based interaction (Macchi and Pisapia 2024). From a Cognitive Load Theory perspective, these additional elements can represent extraneous load—effort not inherent to the task itself but stemming from the medium’s design (Sweller 2012). In contrast, VC is comparatively straightforward; participants merely look at a flat screen and operate conventional input devices. While 2D calls still impose interpretive burdens (e.g., reading facial expressions in small windows), the overall technological complexity is typically lower. Thus: H4 a : VR predicts higher levels of mental load than VC. Cognitive demands do not only dwell from mental effort, but from all extraneous hindrances, including physical load, for example due to the VR HMD weight, low resolution, heat or pressure on the face. Thus: H4 b : VR predicts higher levels of physical load than VC. The elevated cognitive demands of VR may help explain why it can yield greater fatigue, despite its potential benefits. If users spend significant mental energy managing the HMD, orienting their avatar, or adapting to immersive stimuli, fewer resources remain for the substantive elements of the meeting (Bailenson, 2021). Hence, even a positively interactive VR session may produce more exhaustion in certain domains. When the medium itself is demanding, participants’ overall mental energy may deplete faster, translating into general tiredness. H5 a : Mental load mediates the effect of VR vs. VC on general fatigue in a way that VR leads to higher mental load, which in turn leads to higher general fatigue A cognitively taxing platform can undermine motivation by making each interaction feel effortful or cumbersome. Participants may disengage more quickly or feel resistant to further collaboration. H5 b : Mental load mediates the effect of VR vs. VC on motivational fatigue in a way that VR leads to higher mental load, which in turn leads to higher motivational fatigue Social aspects can be a double-edged sword: while VR is socially richer, the additional mental work of navigating avatars and virtual space can lead to increased social strain, particularly for those unfamiliar with immersive systems (Macchi & Pisapia, 2024). H5 c : Mental load mediates the effect of VR vs. VC on social fatigue in a way that VR leads to higher mental load, which in turn leads to higher social fatigue. Strong presence in VR can elevate emotional involvement, yet simultaneously, the strain of coping with technical hurdles (glitches, motion tracking errors) can exacerbate emotional exhaustion. H5 d : Mental load mediates the effect of VR vs. VC on emotional fatigue in a way that VR leads to higher mental load, which in turn leads to higher emotional fatigue Overall, these hypotheses posit two opposing forces at play in VR meetings: the positive path via heightened interactivity and social presence, and the negative path via increased cognitive load (figure 1). Understanding how these forces interact and differentially impact various forms of fatigue provides insight into how best to design and deploy VR for collaborative work. Prolonged HMD use may introduce salient ergonomic stressors—additional mass on the cervical spine, heat and pressure around the face, restricted peripheral vision and sustained near-focus accommodation—that do not occur, or occur only weakly, in VC sessions. According to the Effort–Recovery model of fatigue (Meijman & Mulder, 1998) and research on biomechanical strain (Bongers et al., 2006), such bodily demands continuously consume energetic resources, thereby creating a physical-load pathway through which VR can precipitate multiple forms of exhaustion. Mechanical strain depletes systemic energy reserves and delays physiological recovery, leading to a broad sense of weariness (Trougakos et al., 2014). H6 a : Physical load mediates the effect of VR versus VC on general fatigue, such that higher physical load predicts greater general fatigue. Ergonomic discomfort provokes aversive self-regulatory effort that undermines willingness to persist, consistent with motivational-control accounts of fatigue (Hockey, 2013). H6 b : Physical load mediates the effect of VR versus VC on motivational fatigue, with greater physical load associated with higher motivational fatigue. Physical discomfort elevates irritability and reduces tolerance during social exchange (Lazarus & Folkman, 1984), thereby heightening interpersonal strain. H6 c : Physical load mediates the effect of VR versus VC on social fatigue, such that higher physical load predicts greater social fatigue. Embodied affect research shows that somatic discomfort amplifies negative emotional appraisal and depletion (Zohar et al., 2003). H6 d : Physical load mediates the effect of VR versus VC on emotional fatigue, with greater physical load leading to greater emotional fatigue. Sustained near-focus and display-induced vergence–accommodation conflict overtaxes the oculomotor system, a primary driver of visual tiredness (Sheedy et al., 2003). H6 e : Physical load mediates the effect of VR versus VC on visual fatigue, such that higher physical load predicts greater visual fatigue. Together with the mental-load hypotheses (H5 a–e ), these propositions complete a dual-path model (Figure 1) in which both cognitive and ergonomic demands independently transmit the influence of immersive VR technology onto the multidimensional experience of videoconference fatigue. Methods Sample and study design Participants were recruited from several universities in Germany via an email distribution system combined with a snowball system. Participation in the study was voluntary, and participants gave informed consent before starting. All participants had the option to drop out at any point in the experiment. The sample consisted of N = 102 participants, primary students from Germany. We excluded six participants because they did not complete all parts of the experiment. We also excluded five groups due to major technological failures during the experiment, resulting in a final sample of N = 84. The age of the final sample ranged from 19 to 59 years ( M = 25.28, SD = 5.32 ), comprising 42.9% females and 57.1% males. 36.9% of the participants work full-time (military university students are counted as full-time workers), 2.4% part-time, and 60.7% are students. The experiment required groups of three participants. These groups were randomly assigned to start with either one of two conditions (2x2 within-between design): a VC or a VR meeting (they participated in both meetings in total, but the order was randomized, see Figure 2). For the first condition, starting with the VR meeting, the group was shown an instruction video on how to use the Meta Quest 2 VR head-mounted display (503 g, 1832 * 1920 resolution per eye, 104° horizontal FOV, 98° vertical FOV, 90 Hz refresh rate, head and hand tracking) and how to navigate in the meeting platform used (Horizon Workrooms). The video explained how the HMD can be adjusted on the head and how to navigate in an immersive environment. When the video finished, the participants were instructed to set up the VR HMD on their own, but they were always able to ask a principal investigator for help. After the setup, participants were guided into the VR meeting room, in which they greeted the other participants briefly as part of a connection test (to test the microphone and audio). The connection test was conducted to ensure that the equipment was working correctly for each participant and that participants could operate in the immersive environment. After the connection test, participants were asked to take off the VR HMD. To assure the participants didn’t suffer any cybersickness and had time to make final adjustments with their VR Headset, they were given five-minute rest, before all participants started to fill in a first survey (T1). After filling out the questionnaire, participants started with the first fifteen-minute meeting. Each participant was given a list of names and seating preferences for a company meeting in the meetings. The three participants were given an excel sheet with a seating plan and some room information (Material available on request). They were tasked to seat all imaginary meeting members in a way that most preferences were met. After 15 minutes, participants filled out a second questionnaire (T2) and were then asked to repeat the task in a second meeting (this time in VC if they completed the previous task in VR, or in VR if they completed the previous task in VC, respectively), but with different information distributed. Finally, after the second fifteen-minute meeting, they were asked to complete a final questionnaire (T3). Measures Videoconference fatigue was assessed after the first and second meeting by using a German adaption of the Zoom & Exhaustion Scale (ZEF Scale; (Fauville et al. 2021a), composed of 15 items. General Fatigue describes an overall tiredness and lack of energy (four items); example item: “After participating in the video conference, I feel tired”). Social Fatigue describes weariness and reduced capacity for social interactions (three items); example item: “After participating in the video conference, I avoid social interactions”). Emotional Fatigue describes emotional drain and burnout (four items); example item: “I feel emotionally drained after this meeting”). Motivational Fatigue describes a decline in motivation and enthusiasm for activities or tasks (three items); example item: “After participating in the video conference, I don’t feel like doing anything”), and Visual Fatigue describes strain and discomfort related to the eyes (three items); example item: “After participating in the video conference, my eyes feel irritated”. The items were answered on a 5-point Likert scale (1 = “Not at all” to 5 = “Very much”). Mental load was assessed after the first and second meeting using the German adaption of the mental demand item from the NASA-TLX questionnaire from Hart and Staveland (1988): “How much mental effort was required for the meeting?” (Hart and Staveland 1988). The item was answered on a 10-point Likert scale from 1 = “Low” to 10 = “High” mentally demanding. The aberration from 5 was used to calculate the score. Physical load was assessed after the first and second meeting using the German adaption of the physical demand item from the NASA-TLX questionnaire from Hart and Staveland (1988): “How physically demanding was the task (e.g., for technical operation)?”. Although the NASA-TLX is conventionally used to assess multidimensional workload, the mental demand and physical demand items overlaps strongly with Sweller’s notion of cognitive load, reflecting the effort required to process information and maintain attention. Thus, we adopt NASA-TLX’s mental demand facet as a proxy for cognitive load in line with Cognitive Load Theory. The item was answered on a scale from 21 point Likert scale from 1 = “Very low” to 21 = “Very high”. Positive Interactions were assessed after the first and second meeting using a German adaptation of three items from the positive interaction subscale of the social presence questionnaire from Yoon and Leem (2021), adapted from Kang et al. (2007). An expletory item is “I feel comfortable talking to the participants and exchanging opinions”. The items were answered on a 5-point Likert scale from 1 = “Strongly disagree” to 5 = “Strongly agree”. Technical difficulties during the meetings were assessed after each meeting using a single self-developped item: “There were technical difficulties during the meeting”. This item was answered on a 5-point Likert scale from 1 = “Does not apply at all” to 5 = “Fully applies”. Cronbach’s alphas for all scales are provided in Table 1. Statistical Analysis Structural equation modeling (SEM) with latent constructs (Fornell and Larcker 1981) was performed in R using the lavaan package (Rosseel 2012). Model fit was evaluated via the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA). An autoregressive component controlled for initial fatigue levels, and covariates were sequentially introduced based on their correlations with the outcomes. A significance level of .05 was assumed. Ethics statement and funding All procedures performed in this study were in accordance with the ethical standards of the institution and the 1964 Helsinki Declaration and its later amendments, or comparable ethical standards. Approval is available in the Appendix. This research has received funding by the center of digitalization- and technology research of the military in Germany. Results Descriptives Mean scores of the fatigue facets and their changes from before and after the meetings are displayed in Fig. 3 . All hypotheses were tested using multilevel structural equation modeling, nesting time points (level 1) into participants (level 2). Control Variables were included based on their influence on the outcome variables, as shown in the correlation table (Table 1 ). Because of the significant correlation of Technical Difficulties (TD) with the condition, positive for T2 ( r = .29, p < .001) and negative for T3 ( r = − .29, p = .007), we included TD as a control variable into the model. Table 1 Means, Standard Deviations, and Intercorrelations of Self-Reported Measures M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 1. Condition 1.44 0.50 - 2. Age 25.29 5.32 .12 - 3. Gender 1.43 0.50 − .09 − .02 - 4. Technical Affinity 3.40 1.23 .08 .13 − .38*** - 5. Technical Problems T2 1.68 1.07 .29** − .02 − .08 − .06 - 6. Technical Problems T3 2.33 1.46 − .49*** − .02 .15 − .04 − .13 - 7. General Fatigue T1 2.45 1.12 .25* − .01 .14 − .04 .09 − .03 (.84) 8. General Fatigue T2 2.15 0.99 .21 − .07 .06 − .02 .03 − .05 .67*** (.86) 9. General Fatigue T3 2.27 1.05 − .03 − .09 .12 .02 − .09 .11 .54*** .57*** (.85) 10. Emotional F T1 1.90 0.84 − .02 − .04 .14 .05 − .05 − .02 .70*** .48*** .50*** (.78) 11. Emotional F T2 1.61 0.68 − .01 − .10 .19 .02 − .03 − .06 .54*** .62*** .51*** .71*** (.63) 12. Emotional F T3 1.64 0.80 − .01 − .01 .17 − .05 − .00 .06 .45*** .41*** .68*** .62*** .61*** (.82) 13. Motivational F T1 1.84 0.91 .12 .10 .19 − .33** .02 − .07 .60*** .46*** .51*** .59*** .47*** .50*** (.62) 14. Motivational F T2 1.54 0.79 .02 .06 .13 − .13 .12 .01 .50*** .50*** .40*** .47*** .51*** .50*** .63*** (.68) 15. Motivational F T3 1.52 0.81 .02 .17 .15 − .03 .04 .07 .49*** .39*** .60*** .41*** .41*** .60*** .62*** .72*** (.76) 16. Social F T1 1.89 0.94 .11 − .03 .22* − .11 .08 − .01 .70*** .37*** .36*** .55*** .43*** .33** .61*** .37*** .42*** (.87) 17. Social F T2 1.56 0.66 .17 − .05 .06 .01 .06 − .10 .54*** .53*** .23* .42*** .57*** .27* .38*** .56*** .48*** .61*** (.90) 18. Social F T3 1.53 0.77 − .02 − .04 .11 − .05 − .06 .10 .45*** .33** .60*** .36*** .39*** .59*** .43*** .44*** .69*** .53*** .58*** (.91) 19. Visual F T1 1.62 0.80 − .04 − .11 .11 − .07 .00 .10 .42*** .48*** .48*** .30** .33** .23* .29** .19 .24* .28* .26* .36*** (.81) 20. Visual F T2 1.87 1.06 .25* − .10 − .00 − .02 .07 − .06 .31** .57*** .38*** .16 .26* .22* .20 .17 .24* .09 .31** .27* .67*** (.86) 21. Visual F T3 1.91 1.00 − .20 − .16 .10 − .00 − .03 .38*** .28** .30** .48*** .17 .21 .31** .07 .25* .30** .19 .19 .40*** .51*** .37*** (.86) 22. PI T2 4.36 0.76 .15 .03 .12 − .03 .02 − .01 − .09 − .15 − .06 − .13 − .32** − .14 − .14 − .42*** − .27* − .02 − .43*** − .25* − .12 − .04 − .02 (.85) 23. PI T3 4.34 0.76 − .06 .01 .15 − .03 − .06 − .11 − .06 − .13 − .33** − .05 − .18 − .40*** − .05 − .22* − .40*** − .05 − .24* − .55*** − .08 − .13 − .16 .38*** (.83) 24. Mental Load T2 3.10 2.37 .10 − .16 − .01 − .03 .15 .00 − .13 .07 − .01 − .11 − .07 − .10 − .05 − .02 − .05 .01 − .02 .01 − .01 .12 .01 .16 − .00 - 25. Mental Load T3 3.57 2.56 .07 − .10 − .08 − .07 .11 − .06 − .10 − .02 − .15 − .12 − .08 − .04 − .03 .00 .05 .07 .11 .13 − .15 .00 − .12 .08 − .14 .34** - 26. Physical Load T2 7.36 1.81 − .27* − .09 .02 − .05 − .03 .21 .22* .10 .16 .19 .07 .08 .17 .11 .06 .06 − .06 .13 .05 − .16 .12 .09 .06 − .14 − .03 - 27. Physical Load T3 6.30 2.45 .25* .09 .17 − .32** .15 − .23* .15 .17 − .13 .05 .07 − .07 .15 .05 − .08 − .03 .01 − .19 − .09 .09 − .26* .11 .27* .09 .14 .12 - Note . F = Fatigue. PI = Positive Interaction. Significance levels are displayed with * p < .05, ** p < .01 and *** p < .001. Cronbach’s alphas are displayed in the diagonal brackets. Condition is coded with “1 = Starting Condition VC” and “2 = Starting Condition VR” Hypothesis testing Results of the direct effects used to test H1 a − e are displayed in Table 2 . Mediation effects were tested using the same model. Mediation results are displayed in Table 3 . Since each hypothesis was clearly stated as directional (e.g., “VR leads to higher fatigue than VC”), we tested them one-sided. This approach aligns with recommendations suggesting that when hypotheses are explicitly directional (Rosenthal and Rosnow 2008), the statistical test should be conducted one-sided to avoid interpretational biases. Table 2 Direct effects from the condition on outcome DV IV β SE z p General Fatigue Condition (high = VR) 0.366 0.151 2.423 .015** TD 0.015 0.068 0.223 .824 Positive Interactions -0.498 0.162 -3.081 .002*** Mental Load -0.015 0.036 -0.414 .679 Physical Load 0.028 0.042 0.652 .514 Motivational Fatigue Condition (high = VR) 0.099 0.086 1.148 .251 TD -0.004 0.034 -0.123 .902 Positive Interactions -0.379 0.166 -2.277 .023** Mental Load -0.010 0.021 -0.495 .620 Physical Load 0.018 0.021 0.853 .394 Social Fatigue Condition (high = VR) 0.073 0.072 1.019 .308 TD 0.030 0.039 0.758 .448 Positive Interactions -0.467 0.140 -3.327 .001*** Mental Load 0.007 0.022 0.306 .760 Physical Load 0.030 0.027 1.122 .262 Emotional Fatigue Condition (high = VR) 0.280 0.101 2.774 .006** TD -0.013 0.049 -0.266 .790 Positive Interactions -0.655 0.112 -5.867 .000*** Mental Load 0.014 0.032 0.427 .670 Physical Load -0.006 0.029 -0.205 .837 Visual Fatigue Condition (high = VR) 0.280 0.155 1.809 .070* TD 0.106 0.071 1.501 .133 Positive Interactions -0.121 0.112 -1.074 .283 Mental Load -0.002 0.032 -0.067 .946 Physical Load -0.057 0.035 -1.631 .103 Positive Interactions Condition (high = VR) 0.229 0.098 2.343 .019** TD -0.064 0.045 -1.412 .158 Mental Load Condition (high = VR) 0.003 0.339 0.010 .992 TD 0.085 0.161 0.527 .598 Physical Load Condition (high = VR) -0.989 0.367 -2.695 .007** TD -0.197 0.146 -1.351 .177 Note . Significance levels are displayed with * p < .10, ** p < .05 and *** p < .005. The table shows direct within effects with time nested in persons. TD = Technical Difficulties. β = standardized coefficient. Condition is binary coded (0 = VC; 1 = VR) thus, a positive β indicates higher outcome for VR, lower β indicated higher in VC. In line with H1 a , we observed a significant positive effect of VR on general fatigue ( β = 0.320, p = .021). As predicted by H1 b ( β = 0.074, p = .270) and H1 c ( β = 0.034, p = .345), no significant effects were found for motivational or social fatigue. Regarding H1 d , the effect was again significant and positive ( β = 0.278, p = .006). H1 e , predicting higher visual fatigue in VR, was supported ( β = 0.321, p = .099). Examining H2, we found a significant positive effect on positive interactions ( β = 0.230, p = .019), confirming H2. To examine the direct effects of the condition on mental (H4 a ) and physical (H4 b ) load, we found no significant effect on mental load ( β = 0.003, p = .992) but a significant effect on physical load ( β = -0.989, p = .007). Table 3 Mediation effects DV Mediator β SE z p General Fatigue PI ind −0.098 0.056 −1.758 .079* PI total 0.247 0.150 1.648 .099* ML ind −0.000 0.005 −0.010 .992 ML total 0.345 0.150 2.305 .021** PL ind -0.023 0.040 -0.576 .565 PL total 0.322 0.136 2.368 .018** Motivational Fatigue PI ind −0.082 0.050 −1.636 .102 PI total 0.011 0.077 0.143 .886 ML ind -0.000 0.004 -0.010 .992 ML total 0.093 0.084 1.102 .271 PL ind -0.017 0.021 -0.779 .436 PL total 0.077 0.079 0.971 .331 Social Fatigue PI ind −0.103 0.053 −1.919 .055* PI total -0.035 0.076 -0.460 .646 ML ind −0.004 0.012 −0.309 .757 ML total 0.068 0.072 0.943 .346 PL ind -0.028 0.026 -1.085 .278 PL total 0.039 0.066 0.594 .029** Emotional Fatigue PI ind −0.142 0.064 −2.222 .026** PI total 0.128 0.111 1.151 .250 ML ind 0.000 0.005 0.010 .992 ML total 0.270 0.099 2.725 .006*** PL ind 0.008 0.029 0.279 .780 PL total 0.278 0.099 2.807 .005*** Visual Fatigue PI ind -0.028 0.029 -0.969 .333 PI total 0.252 0.150 1.684 .092* ML ind 0.000 0.001 -0.010 .992 ML total 0.280 0.155 1.808 .071* PL ind 0.056 0.039 1.428 .153 PL total 0.336 0.155 2.171 .030** Note . Significance levels are displayed with * p < .10, ** p < .05 and *** p < .005. The table shows indirect mediation effects from the condition as predictor. Time points are nested in persons. ML = Mental Load. PI = Positive Interactions. PL = Physical Load. Ind = indirect mediation effect. Total = total mediation effect. Positive β indicates higher outcome for VR, lower β indicated higher in VC. In line with H3 a through H3 d , we observed significant mediation effects of positive interactions on general fatigue ( β = -0.044, p = .089), social fatigue ( β = -0.076, p = .053), motivational fatigue ( β = -0.074, p = .118), and emotional fatigue ( β = -0.097, p = .027). Therefore, H3 a , H3 b , and H3 d were supported, while H3 e was rejected. H5 a − d examined whether the condition affected fatigue dimensions through mental load. For general fatigue ( β = -0.007, p = .746), social fatigue ( β = 0.004, p = .781), motivational fatigue ( β = -0.004, p = .757), emotional fatigue ( β = 0.002, p = .211), and visual fatigue ( β = 0.000, p = .992), no significant mediation was found. Consequently, H5 a − d were rejected. H6 a − e examined whether the condition affected fatigue dimensions through physical load. For general fatigue ( β = -0.023, p = .565), motivational fatigue ( β = -0.017, p = 0.436), social fatigue ( β = -0.028, p = .278), emotional fatigue ( β = 0.278, p = .780), and visual fatigue ( β = 0.056, p = .153), no significant mediation was found. Consequently, H6 a − d were rejected. Discussion Our experiment shows that VR meetings significantly increased general, emotional and visual VCF while simultaneously enhancing positive social interaction compared with VC. Our evidence moves beyond Hennig-Thurau et al. (2023) by providing the first experimental demonstration that immersive cues selectively heighten general, emotional, and visual fatigue, thereby specifying the precise blades of the ‘double‑edged sword’ metaphor.” A key goal of our analysis was to identify potential pathways through which VR might elevate/diminish fatigue. The null mediation for both mental (H5 a − e ) and physical load (H6 a − e ) challenges the prevailing cognitive overload account of VCF, indicating that alternative mechanisms must be considered. Although the single-item NASA-TLX proxies warrant caution, the pattern nonetheless invites reconceptualizing VCF research away from an exclusive focus on working-memory depletion toward factors such as the perceived naturalness of communication. In the absence of a „dark path“ to explain fatigue, Media Naturalness Theory (Kock 2004) might offer an alternative lens. Following the theory, not only does the richness of a medium matter, but also the naturalness of the stimuli. A decrease in naturalness of stimuli might heighten its ambiguity. Avatars that lack natural eye movement or facial micro‑expressions may feel “off” or “unnatural” increasing strain even when cognitive effort is not consciously higher. Looking at a 3D rendered face with no natural eye movement (or any other real facial expressions) might be perceived as unnatural, leading to a more straining meeting and therefore fatigue. Even if VR allows for more nonverbal cues, these signals may still appear “off” to users. Additionally, wearing a 503-gram HMD (in this case, the Meta Quest 2) may contribute to physical and general fatigue, especially for participants unaccustomed to such gear. As hypothesized, VR’s immersive attributes yielded more positive social interactions than VC. Spatial audio, the ability to orient oneself in a 360° virtual environment, and greater freedom of movement likely approximated face-to-face dynamics more closely than a 2D platform could. These social benefits, however, did not fully offset the increased fatigue in several domains. Future research may, therefore, investigate whether habituation to VR HMDs reduces fatigue over time. Macchi and Pisapia (2024) suggest that repeated exposure can reduce initial discomfort and learning challenges, implying that novices may not accurately represent the medium’s long-term fatigue effects. Theoretical Implications Firstly, our findings contribute to the ongoing theoretical debate on cognitive and physical load as mechanisms underlying videoconference fatigue. Contrary to prior assumptions, neither mental nor physical load significantly mediated fatigue in VR, suggesting that other factors—such as perceived naturalness or the uncanny quality of avatar communication—may better explain fatigue outcomes. This challenges the dominant cognitive overload account and invites a theoretical reorientation toward affective or perceptual explanations. Secondly, we expand the empirical literature on videoconference fatigue in immersive environments. While previous studies pointed to potential strain in VR, our study is the first to show that specific fatigue facets—namely general, emotional, and visual fatigue—are elevated, whereas motivational and social fatigue remain unaffected. This differentiation underscores the value of a multi-dimensional approach to fatigue. Thirdly, we provide experimental evidence for the positive social affordances of immersive VR, showing that richer social presence and improved interactivity translate into more positive interaction experiences than in VC. This supports media naturalness theory and underlines that immersive environments can enhance perceived interpersonal quality, even when accompanied by fatigue. Fourthly, by adopting a within-subject design, we offer a methodological advancement that allows for more precise estimation of individual responses to different media settings, overcoming limitations of prior between-group studies and strengthening internal validity in VR communication research. Lastly, by implementing a new meeting task focused on structured information sharing rather than creative ideation, we demonstrate that immersive media effects are not limited to design sprints or brainstorming settings, but also extend to more routine, cognitively structured meeting scenarios—thereby broadening the generalizability of prior findings. Practical Implications Firstly, our results show that immersive VR platforms enhance social interaction quality compared to VC, but also lead to higher general, emotional, and visual fatigue. This trade-off should be considered when evaluating VR for everyday team meetings. Secondly, the increase in fatigue occurred even in a structured, non-creative task, suggesting that these effects are not limited to ideation settings and may generalize to broader workplace contexts. Thirdly, participants reported more technical issues and physical strain with VR, pointing to the importance of ergonomic hardware and user support—especially for inexperienced users. Lastly, organizations should consider adaptation time and training when introducing VR, as unfamiliarity may amplify fatigue and reduce the effectiveness of immersive tools in practice. Limitations and Future Research Despite these insights, there are notable limitations. First, we only tested one specific VR HMDs (Meta Quest 2) and platform (Horizon Workrooms), which may not generalize to all immersive technologies. Future research is needed to explicitly test the differences between heavily used HMD, such as comparing the Meta Quest 2 with the Apple Vision Pro HMD. Second, our sample primarily included students whose technology habits or physical fitness levels may differ from the wider workforce. Future studies should address VR applications in real-life work settings and use field experiment designs with end users. Third, the study’s short-term design prevents in-depth analysis of longer-term adaptation or habituation effects. Longitudinal approaches could accompany VR rollouts in organizations to measure both short term and long term effects of use. Fourth, we assessed mental and physical load using a validated questionnaire; however, only single items were utilized, which may not have fully captured the complexity of the constructs. A more fine-grained questionnaire to access cognitive load facets would enhance future studies. Lastly, studies would benefit from diverse populations, multiple VR devices, and repeated-measures designs extending over weeks or months. Moreover, results from Souchet et al. (2023) suggest, that different task types might change the outcomes. Therefore, incorporating different task types into new experimental studies could contribute to the discussion on whether VR can enhance meetings or, conversely, in which contexts VR is most effective. Lastly, we need to address that all scales used in this study are self-reported measures. We did not include physiological measures, which could have added to a more fine-grained analysis of fatigue and cognitive load. Future studies could contribute to the discussion by incorporating physiological measures. In sum, our work demonstrates that VR offers distinct advantages for social interaction yet amplifies certain types of fatigue. Going forward, researchers and practitioners alike must grapple with how best to harness VR’s immersive potential without overburdening users, balancing gains in engagement and communication against the potential for elevated fatigue. Even though we controlled for previous experience with the Meta Quest 2 virtual reality HMD, only a very small sample fragment had some experience, so there is not enough variance in the data. As discussed in the theory, first-time users experience higher levels of fatigue, so we can’t generalize the results to people with moderate to a lot of experience. Lastly, we theorized that the naturalness of stimuli could be essential for fatigue and other important meeting outcomes, like communication quality. However, we did not delve into how participants perceived natural stimuli differently. To our best knowledge, there is no experimental research on how to assess how natural stimuli provided by a media are perceived. Therefore, methodical research is required to shed more light on how media can affect meeting outcomes. Conclusion In conclusion, this study sheds light on the dual nature of VR in remote meetings: on the one hand, it fosters positive social interactions; on the other, it heightens fatigue more than a 2D platform like VC. The absence of significant mediation via cognitive load indicates that other factors—such as physical HMD discomfort or the lack of natural cues—may be key drivers of fatigue instead. Furthermore, researchers could explore the effects of habituation with VR meetings on meeting outcomes and the role of improved hardware solutions. Ultimately, our results underscore the importance of thoughtful implementation: VR holds promise for deeply engaging remote collaboration, provided users’ well-being remains front and center. Declarations Author Contribution Y.F. write the main manuscript, carried out the experiment, made the calculations tables and figuresP.G. assisted in the writing process, carried out the experiment, assisted with the calculation modelsM.G assisted in the writing process, assisted with the calculationsJ.F. assisted in the writing process, assisted with the development of the experiment, assisted in the interpretation of results. Data Availability Data will be provided in the supplementary files. References Bailenson, Jeremy N. (2021): Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. In Technology, Mind, and Behavior 2 (1). DOI: 10.1037/tmb0000030. Brown, Stuart; Taylor, Krista; Siddiqi, Khadija; Shalini, Shruti (2023): Positive energy in the metaverse: A new era of efficiency. Accenture. Available online at https://www.accenture.com/content/dam/accenture/final/industry/energy/document/Accenture-Positive-Energy-In-The-Metaverse.pdf, checked on 5/23/2025. 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In Scientific reports 13 (1), p. 18371. DOI: 10.1038/s41598-023-45374-y. Rosenthal, Robert; Rosnow, Ralph L. (2008): Essentials of behavioral research. Methods and data analysis. 3. ed. Boston: McGraw-Hill (McGraw-Hill higher education). Available online at http://www.loc.gov/catdir/enhancements/fy0702/2006017236-d.html. Rosseel, Yves (2012): lavaan : An R Package for Structural Equation Modeling. In J. Stat. Soft. 48 (2). DOI: 10.18637/jss.v048.i02. Sanchez-Vives, Maria V.; Slater, Mel (2005): From presence to consciousness through virtual reality. In Nature reviews. Neuroscience 6 (4), pp. 332–339. DOI: 10.1038/nrn1651. Slater, Mel (2018): Immersion and the illusion of presence in virtual reality. In British journal of psychology (London, England : 1953) 109 (3), pp. 431–433. DOI: 10.1111/bjop.12305. Slater, Mel; Wilbur, Sylvia (1997): A Framework for Immersive Virtual Environments (FIVE): Speculations on the Role of Presence in Virtual Environments. In Presence: Teleoperators & Virtual Environments 6 (6), pp. 603–616. DOI: 10.1162/pres.1997.6.6.603. Souchet, Alexis D.; Lourdeaux, Domitile; Pagani, Alain; Rebenitsch, Lisa (2023): A narrative review of immersive virtual reality’s ergonomics and risks at the workplace: cybersickness, visual fatigue, muscular fatigue, acute stress, and mental overload. In Virtual Reality 27 (1), pp. 19–50. DOI: 10.1007/s10055-022-00672-0. Sweller, John (1988): Cognitive load during problem solving: Effects on learning. In Cognitive Science 12 (2), pp. 257–285. DOI: 10.1016/0364-0213(88)90023-7. Sweller, John (2012): Cognitive Load Theory: Recent Theoretical Advances. In Jan L. Plass, Roxana Moreno, Roland Brünken (Eds.): Cognitive Load Theory: Cambridge University Press, pp. 29–47. Wiederhold, Brenda K. (2020): Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding "Zoom Fatigue". In Cyberpsychology, behavior and social networking 23 (7), pp. 437–438. DOI: 10.1089/cyber.2020.29188.bkw. Yoon, Pilhyoun; Leem, Junghoon (2021): The Influence of Social Presence in Online Classes Using Virtual Conferencing: Relationships between Group Cohesion, Group Efficacy, and Academic Performance. In Sustainability 13 (4), p. 1988. DOI: 10.3390/su13041988. Additional Declarations No competing interests reported. Supplementary Files data.sav EthicApproval.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7036583","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486468574,"identity":"25c3e350-ef22-4958-9ff4-e0d3d9532975","order_by":0,"name":"Yannick 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09:53:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7036583/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7036583/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87270599,"identity":"d944b80f-1416-4b69-95c4-c6dfb6ffd8c7","added_by":"auto","created_at":"2025-07-22 08:21:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":309697,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGraphical hypothesis overview: “Positive” and “Negative” path\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/2c909d8a710dcb2d916a2af3.jpg"},{"id":87269084,"identity":"bb1046fd-857e-4008-8ecd-25c83bd672a1","added_by":"auto","created_at":"2025-07-22 08:13:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":368792,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eGraphical illustration of the experiment’s procedure\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/179d0f0655ab78497fa67bd6.jpg"},{"id":87269079,"identity":"dab39cbb-a245-4c8d-8dbf-95cb2056827b","added_by":"auto","created_at":"2025-07-22 08:13:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":41521,"visible":true,"origin":"","legend":"\u003cp\u003eFatigue Scores before and after the meetings\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eThe plots illustrate fatigue scale scores recorded before the meeting, after the first meeting (T2), and after the second meeting (T3). \u003cem\u003eVR \u003c/em\u003e= Scale values after Virtual Reality meeting. \u003cem\u003eVC\u003c/em\u003e= Scale values after Microsoft Teams Meeting. \u003cem\u003eT1\u003c/em\u003e = Scale Values before the meetings. \u003cem\u003eT2\u003c/em\u003e = Scale Values after the first meeting. \u003cem\u003eT3\u003c/em\u003e = Scale Values after the second meeting.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/4273cda1012582b7d159112f.jpg"},{"id":87273184,"identity":"1bebcc15-7913-4f57-bfad-8ecbe1c109b8","added_by":"auto","created_at":"2025-07-22 08:37:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2175326,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/e484aa13-b3d4-434c-818f-0eb2e124add0.pdf"},{"id":87269075,"identity":"61af3974-9c1f-4564-b3aa-70ff01673ffb","added_by":"auto","created_at":"2025-07-22 08:13:24","extension":"sav","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":81543,"visible":true,"origin":"","legend":"","description":"","filename":"data.sav","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/ec89b5d6a7e05431a97e55b6.sav"},{"id":87269082,"identity":"c7b2f8da-5db3-43ca-95be-d6681e747d21","added_by":"auto","created_at":"2025-07-22 08:13:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":224328,"visible":true,"origin":"","legend":"","description":"","filename":"EthicApproval.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7036583/v1/be2b4a912756aa2099fb7eb4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Light and Dark Side of VR: A New Hope for Meetings—or Just More Fatigue?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eVideoconferencing (VC) has become essential to modern work (Derouech et al. 2024), allowing dispersed teams to communicate across geographical boundaries. For example, Evans (2020) reported a sharp rise in Zoom usage, growing from about 10 million participants in December 2019 to over 300 million weekly users by April 2020. Likewise, a diary study by Cao et al. (2021) with Microsoft employees, found many of the employees had more meetings than before. Recently, companies have begun to experiment with immersive virtual-reality (VR) meeting platforms that extend the VC continuum by representing participants as three-dimensional avatars (Hennig-Thurau et al. 2023). Fortune 500 firms such as Accenture and PwC are already running onboarding and design-sprint sessions entirely in VR, signaling strong commercial interest in immersive meeting technology (Brown et al. 2023; Hernandez and Rivet 2024). In view of the increase and further development of these technologies, questions about the associated opportunities and risks for performance and health are becoming more important.\u003c/p\u003e\n\u003cp\u003eVC tools such as Microsoft Teams or Zoom offer undeniable benefits, amongst which are reduced travel time, cost savings, and rapid collaboration. However, research has shown that repeated or prolonged use of videoconferencing can provoke adverse outcomes. In particular, a large body of research has focused on so-called \u0026ldquo;videoconference fatigue\u0026rdquo; (Fauville et al. 2021a; Fauville et al. 2021b; Bailenson 2021; Wiederhold 2020; Nesher Shoshan and Wehrt 2022; Riedl et al. 2023), formerly known as \u0026ldquo;zoom fatigue\u0026rdquo;. Videoconference fatigue (VCF) can be defined as \"a feeling of exhaustion from participating in video conference calls\" and may manifest in general (i.e. exhaustion), and more specific emotional, motivational, social, and visual strain (Fauville et al. 2021a). It is an open question, if further technological development, e.g. replacing VC with VR may change the risk of fatigue.\u003c/p\u003e\n\u003cp\u003eSeveral antecedents for VCF have been identified in the VC literature. Bailenson (2021) highlights reduced non‑verbal bandwidth, constant self‑view, and perceived personal‑space invasion which hinder interaction possibilities and he potential role of cognitive load as a explaining mechanisms to VCF. Fauville et al. (2021b) also showed in an experimental study that interpreting nonverbal cues requires more cognitive load which predicts VCF.\u003c/p\u003e\n\u003cp\u003eIt is an open question if upcoming communication technology such as VR platforms could present an alternative that tackle these issues and reduce the risk of VCF. By providing three-dimensional immersive channels, VR has the potential to reduce certain technical limitations of classic videoconference systems. These immersive spaces could offer more possibilities for natural ways of communication and therefore reduce interaction restrictions. For example, in VR environments, participants can maintain direct eye contact in ways that reduce potential misunderstandings, which might lead to clearer social interactions. Furthermore, VR facilitates the perception of spatial relationships and directional audio cues, which could make communication easier. VR offers high levels of immersion, which could foster deeper social contact. However, such an environment could foster cognitive load because of the heightened technical hinderances. For example, reduced resolution, connectivity issues and low wearing comfort require additional cognitive capacity to compensate.\u003c/p\u003e\n\u003cp\u003eWhereas fatigue is well documented for videoconferences, evidence for fatigue with immersive VR meetings is scarce and mixed. We are only aware of two experimental studies that directly compare VC and VR. Macchi and Pisapia (2024) report higher visual strain and emotional fatigue for VR, suggesting more cognitive load, but improved cooperation and openness which may be due to more positive interactions, which describes the received enjoyableness of interacting with one another. Similarly, Hennig-Thurau et al. (2023) found, that VR compared to VC increases positive interactions and social presence, while also increasing emotional fatigue. They conclude that high immersion can be a double-edged sword: while it seems to foster positive interactions due to more realism, it increases exhaustion due to higher demands. These demands include navigating virtual spaces, wearing head-mounted displays (HMD) for prolonged periods, and adapting to unfamiliar avatars and controls also suggesting more cognitive load. However, cognitive load was not assessed in both studies, which makes it unclear whether these increased mental demands with VR may translate in fatigue.\u003c/p\u003e\n\u003cp\u003eHence, current findings cannot explain why particular fatigue facets rise (visual, emotional). Moreover, the effects of VR on other facets (social, motivational, general) have not been examined yet. Guided by cognitive-load theory and social-interaction frameworks, we propose two opposing parallel mediators\u0026mdash;(a) cognitive load and (b) quality of positive social interaction\u0026mdash;that may explain different effects on fatigue subdimensions. As we will argue, VR is associated with higher cognitive load leading to more visual and emotional fatigue, but also associated with better social interactions leading to less social, motivational and general fatigue.\u003c/p\u003e\n\u003cp\u003eThe aim of the present paper is to delve into (a) how VR meetings compare to conventional videoconferences along different facets of fatigue, and (b) whether cognitive load and/or (c) positive interactions mediate these different effects. To test our hypotheses, we conducted a 2 (pre vs. post) x 2 (VC vs. VR) experimental within subject design, in which groups of three participants collaborated in a VC and a VR meeting. To make possible differences between the two media visible, intensive interaction is required in which all participants are highly involved. Therefore, a problem-solving task was chosen in which the participants had different information and goals to accomplish, unlike previous VR-meeting research that has mostly centered on creative ideation or design-sprint tasks.\u003c/p\u003e\n\u003cp\u003eOur study makes several contributions. Firstly, we add to the ongoing theoretical debate\u003c/p\u003e\n\u003cp\u003eof cognitive load as a mediator on fatigue and how to harness the positive aspects of virtual platforms for collaborative work while minimizing the burden of fatigue. Secondly, we expand the methodological approaches to this topic by offering between and within data. By using a within-subject and between-subjects design, we provide novel empirical insights into the specific strengths and weaknesses of immersive communication tools. Third, we respond to recent calls for further research on \u003cem\u003ehow\u003c/em\u003e and \u003cem\u003ewhy\u003c/em\u003e different meeting tools can fatigue participants (REF: Thurau et al., p.14), especially because of the lack of empirical evidence of VCF in VR meetings. Fourth, we also aim to close the literature gap on what specific fatigue facets differ between the use of VC and VR. Lastly, in contrast to prior studies focusing on ideation or design tasks (Macchi and Pisapia 2024; Hennig-Thurau et al. 2023), we implement a new meeting task that emphasizes information sharing and discussion, enabling a more generalizable understanding of interaction demands.\u003c/p\u003e"},{"header":"Theory","content":"\u003cp\u003e\u003cstrong\u003eVideoconference Fatigue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFatigue broadly refers to a state of reduced energy and increased subjective effort that arises after prolonged or intense task engagement (Hockey 2013). Within videoconferencing, VCF describes how individuals feel more physically and socioemotionally exhausted, less motivated, and struggle to concentrate after continuous online meetings (Bailenson 2021; Fauville et al. 2021b).\u003c/p\u003e\n\u003cp\u003eVCF itself can lead to more negative work and health-related outcomes. Excessive fatigue has been linked to lower job satisfaction, decreased performance, and higher stress (Wiederhold 2020). Prolonged videoconferencing can erode psychological well-being, undermining teamwork and collaboration (Cao et al. 2021). Fatigued employees are more prone to burnout and may disengage from work responsibilities, adversely affecting both individual and organizational outcomes (Nesher Shoshan and Wehrt 2022).\u003c/p\u003e\n\u003cp\u003eFauville et al. (2021a) suggest five facets\u0026mdash;general, motivational, social, emotional and visual fatigue\u0026mdash;that vary in intensity depending on the stimuli meeting platforms present. For instance, when users look into a virtual reality head mounted display (HMD), they might see the pixels of the display flicker, which may heighten visual fatigue by forcing the eyes to adapt continuously. Also, the vergence\u0026ndash;accommodation conflict inside head-mounted displays is a well-known driver of visual fatigue (Souchet et al. 2023). Several broad categories help explain the antecedents of videoconference fatigue.\u003c/p\u003e\n\u003cp\u003eFirst, \u003cem\u003etechnological and environmental factors\u003c/em\u003e involve the platform\u0026rsquo;s design, internet connectivity, screen sizes, or camera self-view, all of which force participants to expend extra effort interpreting distorted cues (Nesher Shoshan and Wehrt 2022; Hinds 1999, 1999). However, VR\u0026rsquo;s more natural spatial cues can sometimes ease social or emotional strain compared to two-dimensional grids. Likewise, improvements in bandwidth and camera resolution have reduced latency and pixelation over time (Knoblauch 1999), yet persistent shortcomings\u0026mdash;such as unreliable eye contact and limited spatial cues\u0026mdash;still hamper the realism of traditional videoconferences.\u003c/p\u003e\n\u003cp\u003eSecond, \u003cem\u003einterpersonal and social factors\u003c/em\u003e center on continuous on-camera exposure and perceived close-up interactions that can mimic invasions of personal space, intensifying arousal (Bailenson 2021). While typical video calls may exacerbate self-consciousness, VR\u0026rsquo;s immersive platforms might reduce that pressure by allowing more dynamic, less \u0026ldquo;forced\u0026rdquo; engagements.\u003c/p\u003e\n\u003cp\u003eThird, \u003cem\u003epersonal and cognitive factors\u003c/em\u003e involve individual differences such as attention capacity, self-consciousness, and susceptibility to overstimulation. For instance, users with higher social anxiety or limited familiarity with videoconferencing tools often spend extra mental resources managing the constant stream of visual and auditory input, thereby exacerbating fatigue (Fauville et al. 2021a; Wiederhold 2020; Lim et al. 2025). These studies only glimpse into a wider field of antecedents of VCF. By highlighting the interplay among technology, social dynamics, and personal thresholds, these three categories illustrate how diverse, yet interrelated stressors amplify the experience of videoconference fatigue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVirtual Reality and Immersion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmersion in VR goes beyond merely using a head‑mounted display; it envelops users in multisensory stimuli (Slater 2018). \u003cem\u003ePresence\u003c/em\u003e describes the subjective experience of \u0026ldquo;being there\u0026rdquo; (Slater and Wilbur 1997) whereas \u003cem\u003esocial presence\u003c/em\u003e captures the sense of being \u003cem\u003ewith\u003c/em\u003e others (Gunawardena 1995). From a psychological viewpoint, immersion can be viewed as the system\u0026rsquo;s capability to present an all-encompassing, coherent set of stimuli. At the same time, presence describes the subjective experience of \u0026ldquo;stepping into\u0026rdquo; that reality (Slater 2018). In a VR-based meeting, for example, immersion is supported by 360\u0026deg; head tracking, spatial audio that conveys where voices originate in the virtual space, and motion controllers that capture gestures. The user\u0026rsquo;s \u003cem\u003epresence\u003c/em\u003e emerges when these technological features align seamlessly to create an intuitive, realistic feeling of \u0026ldquo;here and now\u0026rdquo; in a shared space. This VR-mediated sense of presence can only be achieved through the head-mounted display and is described in human-computer interaction literature as qualia (Latoschik \u0026amp; Winriech, 2022).\u003c/p\u003e\n\u003cp\u003eImportantly, immersion has multiple layers. While \u003cem\u003esensory immersion\u003c/em\u003e reflects the hardware\u0026rsquo;s ability to engage users\u0026rsquo; senses comprehensively, \u003cem\u003ecognitive immersion\u003c/em\u003e involves mental engagement, such as when users must process realistic visual depth or track hand movements in three dimensions (Sanchez-Vives and Slater 2005). \u003cem\u003eEmotional immersion\u003c/em\u003e emerges when users feel genuine affective responses\u0026mdash;excitement, empathy, or stress\u0026mdash;prompted by events in the virtual environment (Slater, 2018). In collaborative VR, emotional immersion might intensify due to avatars\u0026rsquo; expressive gestures and the sensation of co-presence with colleagues, potentially heightening both involvement and fatigue (Hennig-Thurau et al., 2023).\u003c/p\u003e\n\u003cp\u003eYet this immersion can cut both ways. Richer, more realistic cues can ease certain communication barriers\u0026mdash;for instance, participants can lean in to show interest or make eye contact that \u0026ldquo;feels real\u0026rdquo;\u0026mdash;enhancing group cohesion and reducing the guesswork associated with nonverbal signals (Kock, 2004). At the same time, these cues can raise cognitive demands, particularly for first-time users who must learn new interaction paradigms like hand controllers or avatar movement (Macchi \u0026amp; Pisapia, 2024). If hardware or software fidelity is lacking\u0026mdash;e.g., lag in tracking, awkward avatar faces\u0026mdash;immersion may feel \u003cem\u003eunnatural\u003c/em\u003e, prompting discomfort or frustration. Physical factors such as the weight of the HMD or heat buildup inside the visor can further strain users, ultimately contributing to different dimensions of fatigue, including visual and emotional overload (Bailenson 2021; Fauville et al. 2021a).\u003c/p\u003e\n\u003cp\u003eIn short, VR aims to reduce the artificiality of remote collaboration by leveraging immersion; however, the degree of immersion hinges on system design, user familiarity, and the realism of the presented stimuli. When well-implemented, immersive features can bring remote communication closer to face-to-face interaction, raising the sense of co-presence and fostering more genuine social interaction. However, as the studies on VCF suggest, these very features can also amplify strains\u0026mdash;especially if the technology is novel or imperfect\u0026mdash;underscoring the need for balanced, user-centric implementations of VR in professional settings. Strains in VR could stem from the novelty of the technology (Macchi and Pisapia 2024), causing the participant to potentially be disoriented in the virtual space and requiring extra effort to identify and navigate through menus and options.\u003c/p\u003e\n\u003cp\u003eGrounded in these theoretical arguments, we propose that the immersive requirements of VR (e.g., donning an HMD, navigating 3D space) impose higher general VFC compared to VC. Thus:\u003c/p\u003e\n\u003cp\u003eH1\u003csup\u003ea\u003c/sup\u003e: VR meetings lead to more general fatigue than VC meetings.\u003c/p\u003e\n\u003cp\u003eImmersive realism can heighten emotional involvement, so even minor technical glitches or self-presentation concerns in VR can feel more intense, contributing to greater emotional drain. Whereas social involvement primarily captures the sense of connectedness and group interaction, emotional involvement focuses on the intensity of personal affective responses\u0026mdash;an aspect that can escalate more readily in highly immersive VR settings, thereby contributing to emotional fatigue. Thus:\u003c/p\u003e\n\u003cp\u003eH1\u003csup\u003eb\u003c/sup\u003e: VR meetings lead to more emotional fatigue than VC meetings.\u003c/p\u003e\n\u003cp\u003eHead-mounted displays demand continuous focus on close-up screens and can introduce optical strain (Macchi and Pisapia 2024). This contrasts with VC, where conventional laptop or desktop screens may be easier on the eyes. Thus:\u003c/p\u003e\n\u003cp\u003eH1\u003csup\u003ec\u003c/sup\u003e: VR meetings lead to more visual fatigue than VC meetings.\u003c/p\u003e\n\u003cp\u003eCognitive Load Theory and Naturalness Theory\u003c/p\u003e\n\u003cp\u003eCognitive Load Theory (Sweller 1988, 2012) contends that limited working‑memory resources are taxed by complex or dense stimuli. When tasks become increasingly complex or stimuli become denser, the cognitive load on individuals rises. Within videoconferencing scenarios, prior studies consistently demonstrate that screen-mediated communication requires substantial concentration to interpret facial expressions, manage technological aspects, and remain self-aware on camera, culminating in heightened fatigue (Bailenson 2021; Fauville et al. 2021b)\u003c/p\u003e\n\u003cp\u003eIn VR meetings, users face novel mental and physical demands, such as operating unfamiliar three-dimensional interfaces, handling head-mounted displays, maintaining spatial orientation, and deciphering avatar movements (Hennig-Thurau et al. 2023; Macchi and Pisapia 2024). For instance, an experimental study by Narasimha et al. (2019) found that participants performing a card sorting task perceived higher mental, physical, and temporal workload, alongside elevated effort and frustration, in VR compared to face-to-face or videoconference conditions. These additional demands may intensify cognitive load, thereby exacerbating fatigue. Indeed, some users in immersive VR sessions report the need to \u0026ldquo;focus extra hard\u0026rdquo; to synchronize head and eye movements with gestural cues\u0026mdash;an effort that can strain mental resources (Macchi and Pisapia 2024). Conversely, while VC calls may present a simpler interface, they still require attention to on-screen cues and can involve overlapping conversations, albeit with fewer immersive stimuli. For example, standard video calls often entail divided attention\u0026mdash;particularly when multiple participants speak simultaneously\u0026mdash;but do not necessitate wearing head-mounted equipment.\u003c/p\u003e\n\u003cp\u003eNaturalness Theory (Kock 2004) posits that communication media offering a closer approximation to face-to-face interactions reduce psychological strain. Since VR often incorporates spatial audio, simulated eye contact, and full-body gestures, it has the potential to deliver more organic social cues than VC, possibly alleviating certain types of cognitive or social friction. Recent work indicates that spatial audio and precise avatar alignment can heighten social presence, streamlining turn-taking and mitigating misunderstandings (Hennig-Thurau et al. 2023; Riedl 2022). However, if immersive features are suboptimal\u0026mdash;e.g., due to low-resolution avatars or delayed head-tracking\u0026mdash;they may ironically become cognitively taxing and emotionally unsettling (Bailenson 2021). Thus, the very qualities intended to enhance realism can inadvertently contribute to fatigue when perceived as insufficiently \u0026ldquo;natural\u0026rdquo; (Fauville et al. 2021b; Fauville et al. 2021a).\u003c/p\u003e\n\u003cp\u003eBoth theories suggest that well-designed VR immersion can reduce certain burdens, such as social awkwardness or misinterpretation of nonverbal signals. Yet incomplete realism or unaccustomed hardware may amplify cognitive load, emotional reactivity, and physical unease\u0026mdash;for instance, extended head-mounted display use can induce eye strain or cybersickness (Macchi and Pisapia 2024). Essentially, VR might ease some media-specific stressors (e.g., difficulty discerning nonverbal cues) while simultaneously adding new sources of strain (e.g., managing bulky equipment), which could accentuate fatigue\u0026mdash;particularly among new adopters (Macchi and Pisapia 2024). Furthermore, the novelty effect of VR\u0026mdash;where initial excitement offsets fatigue\u0026mdash;can diminish with time, or conversely, repeated use may mitigate cognitive overhead as users become more familiar with immersive interfaces (Macchi and Pisapia 2024; Riedl et al. 2023).\u003c/p\u003e\n\u003cp\u003eEmerging research on videoconference fatigue illuminates how these theories intersect. Fauville et al. (2021a), for example, report that persistent self-view in 2D meetings can elevate mental load due to increased self-awareness. Meanwhile, VR typically limits direct self-view, yet requires continuous synchronization of head movements and avatar representation, generating a distinct but comparably high cognitive strain. Moreover, the heightened sense of social presence in VR can intensify emotional involvement, thus exacerbating fatigue when technical disruptions undermine the immersive experience (Hennig-Thurau et al. 2023). These findings underscore that VR\u0026rsquo;s \u0026ldquo;naturalness\u0026rdquo; advantage often depends on technological sophistication and user adaptability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe light path of VR: Positive Interactions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA growing body of research suggests that virtual reality platforms can support richer engagement and more intuitive communication compared to traditional videoconferencing (Hennig-Thurau et al. 2023; Dey et al. 2024; Grabowski et al. 2024; Latoschik and Wienrich 2022). The sense of co-presence, enabled by spatial audio and avatar-based gestures, may increase immediate feedback and nuanced nonverbal cues. This heightened interactivity fosters a stronger perception of social connection, often referred to as social presence (Gunawardena, 1995; Kang et al., 2007). In line with Naturalness Theory (Kock, 2004), these additional sensory channels and real-time cues approximate face-to-face interaction more closely, leading to a smoother flow of conversation and more comfortable group dynamics (Yoon \u0026amp; Leem, 2021).\u003c/p\u003e\n\u003cp\u003eMoreover, immediacy\u0026mdash;the speed and spontaneity of feedback\u0026mdash;can be higher in VR because participants can more effortlessly observe physical orientation and proximity, even if mediated by avatars (Grabowski et al. 2024; Hennig-Thurau et al. 2023). This sense of \u0026ldquo;shared space\u0026rdquo; allows for faster and more organic turn-taking, potentially boosting positive interpersonal outcomes such as perceived friendliness, openness, or collaboration (Gunawardena, 1995; Norton, 1986). By contrast, VC\u0026rsquo;s 2D interface might limit the richness of feedback cues (e.g., reliance on small on-screen windows, less fluid eye contact), potentially leading to lower levels of positive interactivity. Thus:\u003c/p\u003e\n\u003cp\u003eH2: VR leads to more positive interactions than VC.\u003c/p\u003e\n\u003cp\u003eIf VR indeed increases positive interactions, a subsequent question is whether this enhanced sense of engagement and connectivity offsets or mitigates certain dimensions of fatigue. According to social presence theory, heightened interactivity and immediacy can reduce feelings of social awkwardness, boost motivation, and even alleviate emotional strain (Gunawardena, 1995; Kang et al., 2007). Thus, when meetings feel more personal and smoothly interactive, participants may be less likely to experience fatigue\u0026mdash;even if the environment is technologically demanding (Bailenson, 2021). Moreover, in line with the Media Naturalness Theory, a more natural interaction through more natural ways of moving and communicating in VR, could also foster a positive sense of interaction with one another.\u003c/p\u003e\n\u003cp\u003ePositive interactions may help maintain overall energy by making tasks feel more engaging and less monotonous. Even if the medium is demanding, participants who experience a high level of interactive may remain more alert and less fatigued overall. Thus:\u003c/p\u003e\n\u003cp\u003eH3\u003csup\u003ea\u003c/sup\u003e: Positive interactions mediate the effect of VR vs. VC on general fatigue in a way, that VR leads to higher positive interactions which in turn predict less general fatigue.\u003c/p\u003e\n\u003cp\u003eEnhanced social presence and immediate feedback can fuel group cohesion and enthusiasm, encouraging continued effort and reducing the motivational drop-off that often accompanies remote communication (Yoon \u0026amp; Leem, 2021).\u003c/p\u003e\n\u003cp\u003eH3\u003csup\u003eb\u003c/sup\u003e: Positive interactions mediate the effect of VR vs. VC on motivational fatigue in a way, that VR leads to higher positive interactions which in turn predict less motivational fatigue.\u003c/p\u003e\n\u003cp\u003eWhen virtual environments support fluid interaction, social connection could feel more authentic and less contrived. As a result, individuals may be less drained by interpersonal demands (Fauville et al., 2021b).\u003c/p\u003e\n\u003cp\u003eH3\u003csup\u003ec\u003c/sup\u003e: Positive interactions mediate the effect of VR vs. VC on social fatigue in a way, that VR leads to higher positive interactions which in turn predict less social fatigue.\u003c/p\u003e\n\u003cp\u003eHigh positive interactivity can reduce uncertainty, a key driver of emotional exhaustion in online communication (Nesher Shoshan \u0026amp; Wehrt, 2022). Timely nonverbal cues (e.g., nods, facial expressions, gestures) can convey empathy and support, thereby alleviating emotional strain.\u003c/p\u003e\n\u003cp\u003eH3\u003csup\u003ed\u003c/sup\u003e: Positive interactions mediate the effect of VR vs. VC on emotional fatigue in a way, that VR leads to higher positive interactions which in turn predict less emotional fatigue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Dark Path of VR: Cognitive Load \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite VR\u0026rsquo;s potential for richer interactivity, it can also increase cognitive load due to the mental and physical demands of novel hardware (HMD, controllers), the need to track spatial orientation, and the relative novelty of avatar-based interaction (Macchi and Pisapia 2024). From a Cognitive Load Theory perspective, these additional elements can represent extraneous load\u0026mdash;effort not inherent to the task itself but stemming from the medium\u0026rsquo;s design (Sweller 2012). In contrast, VC is comparatively straightforward; participants merely look at a flat screen and operate conventional input devices. While 2D calls still impose interpretive burdens (e.g., reading facial expressions in small windows), the overall technological complexity is typically lower. Thus:\u003c/p\u003e\n\u003cp\u003eH4\u003csup\u003ea\u003c/sup\u003e: VR predicts higher levels of mental load than VC.\u003c/p\u003e\n\u003cp\u003eCognitive demands do not only dwell from mental effort, but from all extraneous hindrances, including physical load, for example due to the VR HMD weight, low resolution, heat or pressure on the face. Thus:\u003c/p\u003e\n\u003cp\u003eH4\u003csup\u003eb\u003c/sup\u003e: VR predicts higher levels of physical load than VC.\u003c/p\u003e\n\u003cp\u003eThe elevated cognitive demands of VR may help explain why it can yield greater fatigue, despite its potential benefits. If users spend significant mental energy managing the HMD, orienting their avatar, or adapting to immersive stimuli, fewer resources remain for the substantive elements of the meeting (Bailenson, 2021). Hence, even a positively interactive VR session may produce more exhaustion in certain domains.\u003c/p\u003e\n\u003cp\u003eWhen the medium itself is demanding, participants\u0026rsquo; overall mental energy may deplete faster, translating into general tiredness.\u003c/p\u003e\n\u003cp\u003eH5\u003csup\u003ea\u003c/sup\u003e: Mental load mediates the effect of VR vs. VC on general fatigue in a way that VR leads to higher mental load, which in turn leads to higher general fatigue\u003c/p\u003e\n\u003cp\u003eA cognitively taxing platform can undermine motivation by making each interaction feel effortful or cumbersome. Participants may disengage more quickly or feel resistant to further collaboration.\u003c/p\u003e\n\u003cp\u003eH5\u003csup\u003eb\u003c/sup\u003e: Mental load mediates the effect of VR vs. VC on motivational fatigue in a way that VR leads to higher mental load, which in turn leads to higher motivational fatigue\u003c/p\u003e\n\u003cp\u003eSocial aspects can be a double-edged sword: while VR is socially richer, the additional mental work of navigating avatars and virtual space can lead to increased social strain, particularly for those unfamiliar with immersive systems (Macchi \u0026amp; Pisapia, 2024).\u003c/p\u003e\n\u003cp\u003eH5\u003csup\u003ec\u003c/sup\u003e: Mental load mediates the effect of VR vs. VC on social fatigue in a way that VR leads to higher mental load, which in turn leads to higher social fatigue.\u003c/p\u003e\n\u003cp\u003eStrong presence in VR can elevate emotional involvement, yet simultaneously, the strain of coping with technical hurdles (glitches, motion tracking errors) can exacerbate emotional exhaustion.\u003c/p\u003e\n\u003cp\u003eH5\u003csup\u003ed\u003c/sup\u003e: Mental load mediates the effect of VR vs. VC on emotional fatigue in a way that VR leads to higher mental load, which in turn leads to higher emotional fatigue\u003c/p\u003e\n\u003cp\u003eOverall, these hypotheses posit two opposing forces at play in VR meetings: the positive path via heightened interactivity and social presence, and the negative path via increased cognitive load (figure 1). Understanding how these forces interact and differentially impact various forms of fatigue provides insight into how best to design and deploy VR for collaborative work.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProlonged HMD use may introduce salient ergonomic stressors\u0026mdash;additional mass on the cervical spine, heat and pressure around the face, restricted peripheral vision and sustained near-focus accommodation\u0026mdash;that do not occur, or occur only weakly, in VC sessions. According to the Effort\u0026ndash;Recovery model of fatigue (Meijman \u0026amp; Mulder, 1998) and research on biomechanical strain (Bongers et al., 2006), such bodily demands continuously consume energetic resources, thereby creating a physical-load pathway through which VR can precipitate multiple forms of exhaustion.\u003c/p\u003e\n\u003cp\u003eMechanical strain depletes systemic energy reserves and delays physiological recovery, leading to a broad sense of weariness (Trougakos et al., 2014).\u003c/p\u003e\n\u003cp\u003eH6\u003csup\u003ea\u003c/sup\u003e: Physical load mediates the effect of VR versus VC on general fatigue, such that higher physical load predicts greater general fatigue.\u003c/p\u003e\n\u003cp\u003eErgonomic discomfort provokes aversive self-regulatory effort that undermines willingness to persist, consistent with motivational-control accounts of fatigue (Hockey, 2013).\u003c/p\u003e\n\u003cp\u003eH6\u003csup\u003eb\u003c/sup\u003e: Physical load mediates the effect of VR versus VC on motivational fatigue, with greater physical load associated with higher motivational fatigue.\u003c/p\u003e\n\u003cp\u003ePhysical discomfort elevates irritability and reduces tolerance during social exchange (Lazarus \u0026amp; Folkman, 1984), thereby heightening interpersonal strain.\u003c/p\u003e\n\u003cp\u003eH6\u003csup\u003ec\u003c/sup\u003e: Physical load mediates the effect of VR versus VC on social fatigue, such that higher physical load predicts greater social fatigue.\u003c/p\u003e\n\u003cp\u003eEmbodied affect research shows that somatic discomfort amplifies negative emotional appraisal and depletion (Zohar et al., 2003).\u003c/p\u003e\n\u003cp\u003eH6\u003csup\u003ed\u003c/sup\u003e: Physical load mediates the effect of VR versus VC on emotional fatigue, with greater physical load leading to greater emotional fatigue.\u003c/p\u003e\n\u003cp\u003eSustained near-focus and display-induced vergence\u0026ndash;accommodation conflict overtaxes the oculomotor system, a primary driver of visual tiredness (Sheedy et al., 2003).\u003c/p\u003e\n\u003cp\u003eH6\u003csup\u003ee\u003c/sup\u003e: Physical load mediates the effect of VR versus VC on visual fatigue, such that higher physical load predicts greater visual fatigue.\u003c/p\u003e\n\u003cp\u003eTogether with the mental-load hypotheses (H5\u003csup\u003ea\u0026ndash;e\u003c/sup\u003e), these propositions complete a dual-path model (Figure 1) in which both cognitive and ergonomic demands independently transmit the influence of immersive VR technology onto the multidimensional experience of videoconference fatigue.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eSample and study design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were recruited from several universities in Germany via an email distribution system combined with a snowball system. Participation in the study was voluntary, and participants gave informed consent before starting. All participants had the option to drop out at any point in the experiment. The sample consisted of \u003cem\u003eN \u003c/em\u003e= 102 participants, primary students from Germany.\u003c/p\u003e\n\u003cp\u003eWe excluded six participants because they did not complete all parts of the experiment. We also excluded five groups due to major technological failures during the experiment, resulting in a final sample of \u003cem\u003eN\u003c/em\u003e = 84. The age of the final sample ranged from 19 to 59 years (\u003cem\u003eM \u003c/em\u003e= 25.28, \u003cem\u003eSD\u003c/em\u003e = 5.32 ), comprising 42.9% females and 57.1% males. 36.9% of the participants work full-time (military university students are counted as full-time workers), 2.4% part-time, and 60.7% are students.\u003c/p\u003e\n\u003cp\u003eThe experiment required groups of three participants. These groups were randomly assigned to start with either one of two conditions (2x2 within-between design): a VC or a VR meeting (they participated in both meetings in total, but the order was randomized, see Figure 2). For the first condition, starting with the VR meeting, the group was shown an instruction video on how to use the Meta Quest 2 VR head-mounted display (503 g, 1832 * 1920 resolution per eye, 104\u0026deg; horizontal FOV, 98\u0026deg; vertical FOV, 90 Hz refresh rate, head and hand tracking) and how to navigate in the meeting platform used (Horizon Workrooms). The video explained how the HMD can be adjusted on the head and how to navigate in an immersive environment. When the video finished, the participants were instructed to set up the VR HMD on their own, but they were always able to ask a principal investigator for help. After the setup, participants were guided into the VR meeting room, in which they greeted the other participants briefly as part of a connection test (to test the microphone and audio). The connection test was conducted to ensure that the equipment was working correctly for each participant and that participants could operate in the immersive environment. After the connection test, participants were asked to take off the VR HMD. To assure the participants didn\u0026rsquo;t suffer any cybersickness and had time to make final adjustments with their VR Headset, they were given five-minute rest, before all participants started to fill in a first survey (T1). After filling out the questionnaire, participants started with the first fifteen-minute meeting. Each participant was given a list of names and seating preferences for a company meeting in the meetings. The three participants were given an excel sheet with a seating plan and some room information (Material available on request). They were tasked to seat all imaginary meeting members in a way that most preferences were met. After 15 minutes, participants filled out a second questionnaire (T2) and were then asked to repeat the task in a second meeting (this time in VC if they completed the previous task in VR, or in VR if they completed the previous task in VC, respectively), but with different information distributed. Finally, after the second fifteen-minute meeting, they were asked to complete a final questionnaire (T3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eVideoconference fatigue\u003c/em\u003e was assessed after the first and second meeting by using a German adaption of the Zoom \u0026amp; Exhaustion Scale (ZEF Scale; (Fauville et al. 2021a), composed of 15 items. General Fatigue describes an overall tiredness and lack of energy (four items); example item: \u0026ldquo;After participating in the video conference, I feel tired\u0026rdquo;). Social Fatigue describes weariness and reduced capacity for social interactions (three items); example item: \u0026ldquo;After participating in the video conference, I avoid social interactions\u0026rdquo;). Emotional Fatigue describes emotional drain and burnout (four items); example item: \u0026ldquo;I feel emotionally drained after this meeting\u0026rdquo;). Motivational Fatigue describes a decline in motivation and enthusiasm for activities or tasks (three items); example item: \u0026ldquo;After participating in the video conference, I don\u0026rsquo;t feel like doing anything\u0026rdquo;), and Visual Fatigue describes strain and discomfort related to the eyes (three items); example item: \u0026ldquo;After participating in the video conference, my eyes feel irritated\u0026rdquo;. The items were answered on a 5-point Likert scale (1 = \u0026ldquo;Not at all\u0026rdquo; to 5 = \u0026ldquo;Very much\u0026rdquo;).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMental load\u003c/em\u003e was assessed after the first and second meeting using the German adaption of the mental demand item from the NASA-TLX questionnaire from Hart and Staveland (1988): \u0026ldquo;How much mental effort was required for the meeting?\u0026rdquo; (Hart and Staveland 1988). The item was answered on a 10-point Likert scale from 1 = \u0026ldquo;Low\u0026rdquo; to 10 = \u0026ldquo;High\u0026rdquo; mentally demanding. The aberration from 5 was used to calculate the score.\u003c/p\u003e\n\u003cp\u003ePhysical load was assessed after the first and second meeting using the German adaption of the physical demand item from the NASA-TLX questionnaire from Hart and Staveland (1988): \u0026ldquo;How physically demanding was the task (e.g., for technical operation)?\u0026rdquo;. Although the NASA-TLX is conventionally used to assess multidimensional workload, the mental demand and physical demand items overlaps strongly with Sweller\u0026rsquo;s notion of cognitive load, reflecting the effort required to process information and maintain attention. Thus, we adopt NASA-TLX\u0026rsquo;s mental demand facet as a proxy for cognitive load in line with Cognitive Load Theory. The item was answered on a scale from 21 point Likert scale from 1 = \u0026ldquo;Very low\u0026rdquo; to 21 = \u0026ldquo;Very high\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePositive Interactions\u003c/em\u003e were assessed after the first and second meeting using a German adaptation of three items from the positive interaction subscale of the social presence questionnaire from Yoon and Leem (2021), adapted from Kang et al. (2007). An expletory item is \u0026ldquo;I feel comfortable talking to the participants and exchanging opinions\u0026rdquo;. The items were answered on a 5-point Likert scale from 1 = \u0026ldquo;Strongly disagree\u0026rdquo; to 5 = \u0026ldquo;Strongly agree\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTechnical\u003c/em\u003e\u003cem\u003edifficulties\u003c/em\u003e during the meetings were assessed after each meeting using a single self-developped item: \u0026ldquo;There were technical difficulties during the meeting\u0026rdquo;. This item was answered on a 5-point Likert scale from 1 = \u0026ldquo;Does not apply at all\u0026rdquo; to 5 = \u0026ldquo;Fully applies\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eCronbach\u0026rsquo;s alphas for all scales are provided in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStructural equation modeling (SEM) with latent constructs (Fornell and Larcker 1981) was performed in R using the \u003cem\u003elavaan\u003c/em\u003e package (Rosseel 2012). Model fit was evaluated via the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA). An autoregressive component controlled for initial fatigue levels, and covariates were sequentially introduced based on their correlations with the outcomes. A significance level of .05 was assumed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement and funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study were in accordance with the ethical standards of the institution and the 1964 Helsinki Declaration and its later amendments, or comparable ethical standards. Approval is available in the Appendix.\u003c/p\u003e\n\u003cp\u003eThis research has received funding by the \u003cem\u003ecenter of digitalization- and technology research of the military \u003c/em\u003ein Germany.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eDescriptives\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMean scores of the fatigue facets and their changes from before and after the meetings are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAll hypotheses were tested using multilevel structural equation modeling, nesting time points (level 1) into participants (level 2). Control Variables were included based on their influence on the outcome variables, as shown in the correlation table (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Because of the significant correlation of \u003cem\u003eTechnical Difficulties\u003c/em\u003e (TD) with the condition, positive for T2 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) and negative for T3 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.007), we included TD as a control variable into the model.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eMeans, Standard Deviations, and Intercorrelations of Self-Reported Measures\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"30\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c25\" colnum=\"25\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c26\" colnum=\"26\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c27\" colnum=\"27\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c28\" colnum=\"28\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c29\" colnum=\"29\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c30\" colnum=\"30\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c16\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c17\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c18\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c19\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c20\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c21\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c22\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c23\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c24\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c25\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c26\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c27\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c28\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c29\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c30\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1. Condition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2. Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3. Gender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4. Technical Affinity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5. Technical Problems T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.29**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6. Technical Problems T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.49***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7. General Fatigue T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e(.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8. General Fatigue T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.67***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e(.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9. General Fatigue T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.54***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.57***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e(.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10. Emotional F T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.70***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.48***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.50***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e(.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11. Emotional F T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.54***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.62***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.51***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.71***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e(.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12. Emotional F T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.45***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.41***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.68***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.62***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.61***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e(.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13. Motivational F T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.60***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.46***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.51***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.59***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.47***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.50***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e(.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14. Motivational F T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.50***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.50***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.40***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.47***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.51***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.50***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.63***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e(.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15. Motivational F T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.49***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.39***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.60***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.41***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.41***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.60***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.62***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.72***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e(.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16. Social F T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.22*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.70***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.37***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.36***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.55***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.43***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.61***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.37***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.42***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e(.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17. Social F T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.54***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.53***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.23*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.42***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.57***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.27*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.56***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.48***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.61***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e(.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18. Social F T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.45***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.60***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.36***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.39***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.59***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.43***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.44***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.69***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.53***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.58***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e(.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19. Visual F T1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.42***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.48***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.48***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.30**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.23*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.29**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.24*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.28*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.26*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.36***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e(.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20. Visual F T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.31**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.57***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.26*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.22*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.24*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.31**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.27*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e.67***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e(.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21. Visual F T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.28**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.30**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.48***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.31**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.30**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.40***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e.51***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e.37***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e(.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22. PI T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.32**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.42***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.27*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.43***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e(.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23. PI T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.33**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.40***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.22*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.40***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.24*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.55***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u003cp\u003e(.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24. Mental Load T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25. Mental Load T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u003cp\u003e.34**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e26. Physical Load T2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.27*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.22*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u003cp\u003e.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e27. Physical Load T3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.32**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.23*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u003cp\u003e.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c20\"\u003e\u003cp\u003e.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c21\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c22\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c23\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c24\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.26*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c25\"\u003e\u003cp\u003e.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c26\"\u003e\u003cp\u003e.27*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c27\"\u003e\u003cp\u003e.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c28\"\u003e\u003cp\u003e.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c29\"\u003e\u003cp\u003e.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c30\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"30\"\u003e\u003cb\u003eNote\u003c/b\u003e. \u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Fatigue. \u003cem\u003ePI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Positive Interaction. Significance levels are displayed with * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01 and *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Cronbach\u0026rsquo;s alphas are displayed in the diagonal brackets. Condition is coded with \u0026ldquo;1\u0026thinsp;=\u0026thinsp;Starting Condition VC\u0026rdquo; and \u0026ldquo;2\u0026thinsp;=\u0026thinsp;Starting Condition VR\u0026rdquo;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHypothesis testing\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003cp\u003eResults of the direct effects used to test H1\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;e\u003c/sup\u003e are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Mediation effects were tested using the same model. Mediation results are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Since each hypothesis was clearly stated as directional (e.g., \u0026ldquo;VR leads to higher fatigue than VC\u0026rdquo;), we tested them one-sided. This approach aligns with recommendations suggesting that when hypotheses are explicitly directional (Rosenthal and Rosnow 2008), the statistical test should be conducted one-sided to avoid interpretational biases.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eDirect effects from the condition on outcome\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ez\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.015**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.824\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.002***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.414\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.679\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.514\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotivational Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.251\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.902\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.277\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.023**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.620\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.853\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.394\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.308\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.448\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.001***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.262\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.006**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.790\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.867\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.000***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.427\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.670\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.205\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.837\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVisual Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.070*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.133\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.283\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.946\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.631\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.103\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive Interactions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.019**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.412\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.158\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMental Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.598\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCondition (high\u0026thinsp;=\u0026thinsp;VR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.695\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.007**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.177\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e. Significance levels are displayed with * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.10, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 and *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.005. The table shows direct within effects with time nested in persons. \u003cem\u003eTD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Technical Difficulties. \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;standardized coefficient. Condition is binary coded (0\u0026thinsp;=\u0026thinsp;VC; 1\u0026thinsp;=\u0026thinsp;VR) thus, a positive \u003cem\u003eβ\u003c/em\u003e indicates higher outcome for VR, lower \u003cem\u003eβ indicated higher in VC.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn line with H1\u003csup\u003ea\u003c/sup\u003e, we observed a significant positive effect of VR on general fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.320, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.021). As predicted by H1\u003csup\u003eb\u003c/sup\u003e (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.074, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.270) and H1\u003csup\u003ec\u003c/sup\u003e (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.345), no significant effects were found for motivational or social fatigue. Regarding H1\u003csup\u003ed\u003c/sup\u003e, the effect was again significant and positive (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.278, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.006). H1\u003csup\u003ee\u003c/sup\u003e, predicting higher visual fatigue in VR, was supported (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.321, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.099). Examining H2, we found a significant positive effect on positive interactions (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.230, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.019), confirming H2. To examine the direct effects of the condition on mental (H4\u003csup\u003ea\u003c/sup\u003e) and physical (H4\u003csup\u003eb\u003c/sup\u003e) load, we found no significant effect on mental load (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.992) but a significant effect on physical load (\u003cem\u003eβ\u003c/em\u003e = -0.989, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.007).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eMediation effects\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMediator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ez\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;1.758\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.079*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.099*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.021**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.018**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMotivational Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;1.636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.886\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.271\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.779\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.436\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.971\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.331\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSocial Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;1.919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.055*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.460\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.646\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;0.309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.757\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.346\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.278\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.594\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.029**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;0.142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026minus;2.222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.026**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.725\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.006***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.780\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.807\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.005***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVisual Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.333\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.092*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.992\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eML total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.071*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL ind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.153\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePL total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.030**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e. Significance levels are displayed with * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.10, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 and *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.005. The table shows indirect mediation effects from the condition as predictor. Time points are nested in persons. \u003cem\u003eML\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Mental Load. \u003cem\u003ePI\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Positive Interactions. \u003cem\u003ePL\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Physical Load. \u003cem\u003eInd\u003c/em\u003e\u0026thinsp;=\u0026thinsp;indirect mediation effect. \u003cem\u003eTotal\u003c/em\u003e\u0026thinsp;=\u0026thinsp;total mediation effect. Positive \u003cem\u003eβ\u003c/em\u003e indicates higher outcome for VR, lower \u003cem\u003eβ indicated higher in VC.\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn line with H3\u003csup\u003ea\u003c/sup\u003e through H3\u003csup\u003ed\u003c/sup\u003e, we observed significant mediation effects of positive interactions on general fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.044, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.089), social fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.076, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.053), motivational fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.074, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.118), and emotional fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.097, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.027). Therefore, H3\u003csup\u003ea\u003c/sup\u003e, H3\u003csup\u003eb\u003c/sup\u003e, and H3\u003csup\u003ed\u003c/sup\u003e were supported, while H3\u003csup\u003ee\u003c/sup\u003e was rejected.\u003c/p\u003e\u003cp\u003eH5\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;d\u003c/sup\u003e examined whether the condition affected fatigue dimensions through mental load. For general fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.007, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.746), social fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.781), motivational fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.004, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.757), emotional fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.211), and visual fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.992), no significant mediation was found. Consequently, H5\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;d\u003c/sup\u003e were rejected.\u003c/p\u003e\u003cp\u003eH6\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;e\u003c/sup\u003e examined whether the condition affected fatigue dimensions through physical load. For general fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.023, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.565), motivational fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.017, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.436), social fatigue (\u003cem\u003eβ\u003c/em\u003e = -0.028, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.278), emotional fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.278, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.780), and visual fatigue (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.056, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.153), no significant mediation was found. Consequently, H6\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;d\u003c/sup\u003e were rejected.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur experiment shows that VR meetings significantly increased general, emotional and visual VCF while simultaneously enhancing positive social interaction compared with VC. Our evidence moves beyond Hennig-Thurau et al. (2023) by providing the first experimental demonstration that immersive cues selectively heighten general, emotional, and visual fatigue, thereby specifying the precise blades of the \u0026lsquo;double‑edged sword\u0026rsquo; metaphor.\u0026rdquo;\u003c/p\u003e\u003cp\u003eA key goal of our analysis was to identify potential pathways through which VR might elevate/diminish fatigue. The null mediation for both mental (H5\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;e\u003c/sup\u003e) and physical load (H6\u003csup\u003ea\u0026thinsp;\u0026minus;\u0026thinsp;e\u003c/sup\u003e) challenges the prevailing cognitive overload account of VCF, indicating that alternative mechanisms must be considered. Although the single-item NASA-TLX proxies warrant caution, the pattern nonetheless invites reconceptualizing VCF research away from an exclusive focus on working-memory depletion toward factors such as the perceived naturalness of communication.\u003c/p\u003e\u003cp\u003eIn the absence of a \u0026bdquo;dark path\u0026ldquo; to explain fatigue, Media Naturalness Theory (Kock 2004) might offer an alternative lens. Following the theory, not only does the richness of a medium matter, but also the naturalness of the stimuli. A decrease in naturalness of stimuli might heighten its ambiguity. Avatars that lack natural eye movement or facial micro‑expressions may feel \u0026ldquo;off\u0026rdquo; or \u0026ldquo;unnatural\u0026rdquo; increasing strain even when cognitive effort is not consciously higher. Looking at a 3D rendered face with no natural eye movement (or any other \u003cem\u003ereal\u003c/em\u003e facial expressions) might be perceived as unnatural, leading to a more straining meeting and therefore fatigue. Even if VR allows for more nonverbal cues, these signals may still appear \u0026ldquo;off\u0026rdquo; to users. Additionally, wearing a 503-gram HMD (in this case, the Meta Quest 2) may contribute to physical and general fatigue, especially for participants unaccustomed to such gear.\u003c/p\u003e\u003cp\u003eAs hypothesized, VR\u0026rsquo;s immersive attributes yielded more positive social interactions than VC. Spatial audio, the ability to orient oneself in a 360\u0026deg; virtual environment, and greater freedom of movement likely approximated face-to-face dynamics more closely than a 2D platform could. These social benefits, however, did not fully offset the increased fatigue in several domains. Future research may, therefore, investigate whether habituation to VR HMDs reduces fatigue over time. Macchi and Pisapia (2024) suggest that repeated exposure can reduce initial discomfort and learning challenges, implying that novices may not accurately represent the medium\u0026rsquo;s long-term fatigue effects.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTheoretical Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFirstly, our findings contribute to the ongoing theoretical debate on cognitive and physical load as mechanisms underlying videoconference fatigue. Contrary to prior assumptions, neither mental nor physical load significantly mediated fatigue in VR, suggesting that other factors\u0026mdash;such as perceived naturalness or the uncanny quality of avatar communication\u0026mdash;may better explain fatigue outcomes. This challenges the dominant cognitive overload account and invites a theoretical reorientation toward affective or perceptual explanations. Secondly, we expand the empirical literature on videoconference fatigue in immersive environments. While previous studies pointed to potential strain in VR, our study is the first to show that specific fatigue facets\u0026mdash;namely general, emotional, and visual fatigue\u0026mdash;are elevated, whereas motivational and social fatigue remain unaffected. This differentiation underscores the value of a multi-dimensional approach to fatigue. Thirdly, we provide experimental evidence for the positive social affordances of immersive VR, showing that richer social presence and improved interactivity translate into more positive interaction experiences than in VC. This supports media naturalness theory and underlines that immersive environments can enhance perceived interpersonal quality, even when accompanied by fatigue. Fourthly, by adopting a within-subject design, we offer a methodological advancement that allows for more precise estimation of individual responses to different media settings, overcoming limitations of prior between-group studies and strengthening internal validity in VR communication research. Lastly, by implementing a new meeting task focused on structured information sharing rather than creative ideation, we demonstrate that immersive media effects are not limited to design sprints or brainstorming settings, but also extend to more routine, cognitively structured meeting scenarios\u0026mdash;thereby broadening the generalizability of prior findings.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePractical Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFirstly, our results show that immersive VR platforms enhance social interaction quality compared to VC, but also lead to higher general, emotional, and visual fatigue. This trade-off should be considered when evaluating VR for everyday team meetings. Secondly, the increase in fatigue occurred even in a structured, non-creative task, suggesting that these effects are not limited to ideation settings and may generalize to broader workplace contexts. Thirdly, participants reported more technical issues and physical strain with VR, pointing to the importance of ergonomic hardware and user support\u0026mdash;especially for inexperienced users. Lastly, organizations should consider adaptation time and training when introducing VR, as unfamiliarity may amplify fatigue and reduce the effectiveness of immersive tools in practice.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Research\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite these insights, there are notable limitations. First, we only tested one specific VR HMDs (Meta Quest 2) and platform (Horizon Workrooms), which may not generalize to all immersive technologies. Future research is needed to explicitly test the differences between heavily used HMD, such as comparing the Meta Quest 2 with the Apple Vision Pro HMD.\u003c/p\u003e\u003cp\u003eSecond, our sample primarily included students whose technology habits or physical fitness levels may differ from the wider workforce. Future studies should address VR applications in real-life work settings and use field experiment designs with end users.\u003c/p\u003e\u003cp\u003eThird, the study\u0026rsquo;s short-term design prevents in-depth analysis of longer-term adaptation or habituation effects. Longitudinal approaches could accompany VR rollouts in organizations to measure both short term and long term effects of use.\u003c/p\u003e\u003cp\u003eFourth, we assessed mental and physical load using a validated questionnaire; however, only single items were utilized, which may not have fully captured the complexity of the constructs. A more fine-grained questionnaire to access cognitive load facets would enhance future studies.\u003c/p\u003e\u003cp\u003eLastly, studies would benefit from diverse populations, multiple VR devices, and repeated-measures designs extending over weeks or months. Moreover, results from Souchet et al. (2023) suggest, that different task types might change the outcomes. Therefore, incorporating different task types into new experimental studies could contribute to the discussion on whether VR can enhance meetings or, conversely, in which contexts VR is most effective. Lastly, we need to address that all scales used in this study are self-reported measures. We did not include physiological measures, which could have added to a more fine-grained analysis of fatigue and cognitive load. Future studies could contribute to the discussion by incorporating physiological measures.\u003c/p\u003e\u003cp\u003eIn sum, our work demonstrates that VR offers distinct advantages for social interaction yet amplifies certain types of fatigue. Going forward, researchers and practitioners alike must grapple with how best to harness VR\u0026rsquo;s immersive potential without overburdening users, balancing gains in engagement and communication against the potential for elevated fatigue.\u003c/p\u003e\u003cp\u003eEven though we controlled for previous experience with the Meta Quest 2 virtual reality HMD, only a very small sample fragment had some experience, so there is not enough variance in the data. As discussed in the theory, first-time users experience higher levels of fatigue, so we can\u0026rsquo;t generalize the results to people with moderate to a lot of experience.\u003c/p\u003e\u003cp\u003eLastly, we theorized that the naturalness of stimuli could be essential for fatigue and other important meeting outcomes, like communication quality. However, we did not delve into how participants perceived natural stimuli differently. To our best knowledge, there is no experimental research on how to assess how natural stimuli provided by a media are perceived. Therefore, methodical research is required to shed more light on how media can affect meeting outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study sheds light on the dual nature of VR in remote meetings: on the one hand, it fosters positive social interactions; on the other, it heightens fatigue more than a 2D platform like VC. The absence of significant mediation via cognitive load indicates that other factors\u0026mdash;such as physical HMD discomfort or the lack of natural cues\u0026mdash;may be key drivers of fatigue instead. Furthermore, researchers could explore the effects of habituation with VR meetings on meeting outcomes and the role of improved hardware solutions. Ultimately, our results underscore the importance of thoughtful implementation: VR holds promise for deeply engaging remote collaboration, provided users\u0026rsquo; well-being remains front and center.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.F. write the main manuscript, carried out the experiment, made the calculations tables and figuresP.G. assisted in the writing process, carried out the experiment, assisted with the calculation modelsM.G assisted in the writing process, assisted with the calculationsJ.F. assisted in the writing process, assisted with the development of the experiment, assisted in the interpretation of results.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData will be provided in the supplementary files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBailenson, Jeremy N. 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Plass, Roxana Moreno, Roland Br\u0026uuml;nken (Eds.): Cognitive Load Theory: Cambridge University Press, pp.\u0026nbsp;29\u0026ndash;47.\u003c/li\u003e\n\u003cli\u003eWiederhold, Brenda K. (2020): Connecting Through Technology During the Coronavirus Disease 2019 Pandemic: Avoiding \"Zoom Fatigue\". In \u003cem\u003eCyberpsychology, behavior and social networking \u003c/em\u003e23 (7), pp.\u0026nbsp;437\u0026ndash;438. DOI: 10.1089/cyber.2020.29188.bkw.\u003c/li\u003e\n\u003cli\u003eYoon, Pilhyoun; Leem, Junghoon (2021): The Influence of Social Presence in Online Classes Using Virtual Conferencing: Relationships between Group Cohesion, Group Efficacy, and Academic Performance. In \u003cem\u003eSustainability \u003c/em\u003e13 (4), p.\u0026nbsp;1988. DOI: 10.3390/su13041988.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7036583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7036583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"As videoconferencing (VC) has become a pillar of modern collaboration, studies have shown the downsides of engaging in—particularly videoconference fatigue (VCF), a multidimensional construct encompassing general, emotional, motivational, social, and visual exhaustion. Immersive virtual reality (VR) platforms, which promise more natural and socially rich interactions, have been proposed as a possible solution. However, due to the novelty of this quickly evolving technology, the psychological effects of VR meetings remain underexplored. This study investigates how VR and VC meetings differentially affect VCF, and whether cognitive load and positive meeting interactions mediate these effects.\nWe conducted a within-subject experiment (N = 84), where participants completed two 15-minute collaborative meetings—one via Microsoft Teams (VC condition) and one via Meta Quest 2 VR headsets in Horizon Workrooms (VR condition). The meetings involved a problem-solving task requiring information sharing among team members. After each meeting, participants reported levels of five fatigue dimensions, mental and physical load (as proxies for cognitive load), and the quality of positive interactions. Structural equation modeling was used to test direct and indirect effects of meeting condition on fatigue outcomes.\nFindings revealed a dual effect of VR: while participants reported significantly more general, emotional, and visual fatigue in VR compared to VC, they also experienced more positive social interactions. Surprisingly, mental and physical load did not mediate these effects, contradicting established theories that emphasize cognitive overload as the main driver of VCF. Instead, positive interactions partially mediated reductions in social and motivational fatigue in VR, suggesting immersive features may foster more engaging and socially satisfying communication, even as other fatigue dimensions increase.\nThese results refine our understanding of fatigue in immersive contexts. The data suggest that cognitive load may not be the driver of the negative effects of VR meetings This challenges the dominant cognitive load perspective and highlights the importance of perceptual and affective mechanisms, and moreover points out the question: What are the negative drivers of VCF in VR?\nThe study contributes theoretically by disentangling multiple dimensions of VCF, advancing a dual-path model of immersive meeting outcomes, and providing experimental evidence. Practically, it suggests that VR may enhance interaction quality but simultaneously increase fatigue, posing a trade-off for organizations adopting immersive tools. Careful implementation, user onboarding, ergonomic design, and task alignment will be critical for sustainable use.\nFuture work should examine longer-term adaptation, diverse VR hardware, physiological measures of fatigue, and different task types to determine under what conditions VR meetings can offer net benefits without compromising user well-being.\n ","manuscriptTitle":"The Light and Dark Side of VR: A New Hope for Meetings—or Just More Fatigue?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-22 08:13:19","doi":"10.21203/rs.3.rs-7036583/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"237a3304-3cbc-4526-bef0-2152225150be","owner":[],"postedDate":"July 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T09:12:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-22 08:13:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7036583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7036583","identity":"rs-7036583","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}