Going with the flow:
The effects of VR gaming on spatial presence, flow, and positive emotions
Melissa Quirijnen 11219432
University of Amsterdam Graduate School of Communication
Drs. Ewa Międzobrodzka 6963 words 1st of July 2022
Over the past years, virtual reality (VR) gaming gained popularity. VR allows for a 360- degree view of the gaming world, enabling a more immersive gaming experience than desktop games. This affordance of VR gaming may have an impact on various psychological outcomes, such as experiencing emotions during gameplay. This study aimed to investigate the underlying mechanisms of experiencing positive emotions in VR games. This
experimental lab study was conducted among 68 university students who were randomly assigned to play a game either in VR or desktop mode for 25 minutes followed by a
questionnaire about positive emotions, spatial presence, and flow. The results indicated that VR gaming did not lead to an increase in positive emotions. However, the effect of VR gaming on positive emotions was serial mediated through spatial presence and flow. VR gaming led to higher spatial presence, which was related to higher feelings of flow, which subsequently predicted a higher level of positive emotions. This study provides new insights into the VR gaming effects on positive emotions and two possible underlying mechanisms.
Implications of these results for future research are discussed.
Keywords: video games, virtual reality, positive emotions, spatial presence, flow
Virtual reality (VR) is a new phenomenon that is taking the gaming world by storm. In the last year, the VR gaming industry has had a revenue increase of 31.7% (PwC, 2021). What sets VR games apart from gaming played on screens is that VR allows for a 360-degree view of the virtual world, which does not end at the edge of the screen. These technical differences can explain experiencing different psychological outcomes when comparing the effects of VR gaming sessions to ‘traditional’ gaming on desktops, televisions, and phones,
With the popularity of VR gaming rising, the academic interest and field on this topic started to grow (Markowitz & Bailenson, 2021; Freina & Ott, 2015). VR gaming can be a tool for improving emotional well-being by increasing positive emotions and decreasing negative emotions (Pallavicini & Pepe, 2020). Furthermore, VR gaming can provoke higher emotional states than desktop gaming (Lemmens et al., 2021). In their paper, the authors found that in VR, participants experienced stronger negative emotions, such as fear and hostility, as compared with desktop gaming. However, until now little is known about the possible underlying mechanisms of such effects in VR gaming vs desktop gaming on
experiencing —positive emotions—. Therefore, this study aims to fill in this research gap by studying two mediators: spatial presence and flow as underlying mechanisms of the effects of VR vs desktop gaming on positive emotions.
The first proposed mediator—spatial presence—is the notion of ‘feeling of being there’ in a game (Tamborini & Skalski, 2006) and is a significant predictor of emotional states in virtual environments (Riva et al. 2007). Thus, if a medium is unable to induce spatial presence, the emotional responses to the content might be lower. Hence, the current study investigates whether the effect of VR gaming on experiencing positive emotions may be mediated by spatial presence. The second proposed mediator in the current study is —flow—, which is an optimal experience of engagement in a challenging activity (Weber et al., 2009).
Flow proved to cause changes in various brain regions, such as the amygdala and insula, which are linked to positive and negative emotions (Klasen et al., 2012). In view of that, the current study will examine whether the effect of VR gaming on experiencing positive
emotions may be mediated by flow. Taken together, the current study aims to investigate how VR gaming influences experiencing positive emotions and to what extent this relationship is mediated by spatial presence and flow, leading to the following question:
RQ: To what extent does VR gaming vs desktop gaming influence experiencing positive emotions in adults? To what extent is this effect mediated by spatial presence and flow?
VR gaming improves emotional well-being (Pallavicini & Pepe, 2020) and amplifies positive emotions (Pallavinci & Pepe, 2019). Additionally, the manipulation of color and music in virtual environments leads to an increase in positive emotions, such as tenderness and anguish (Lorenzetti et al., 2018). It is important to take a closer look at the mechanisms that may underlie this effect. In the context of VR gaming, spatial presence is a relevant phenomenon that mediates the relationship between VR gaming and the negative emotions of fear and hostility (Lemmens et al. 2021). However, until now, there is little research that investigated to what extent spatial presence may mediate the effects of VR gaming on experiencing positive emotions. Therefore, studying the mediating effect of spatial presence in this context would fill this research gap, allowing a broader view of the academic field of the overall effect of VR gaming on emotions. Further, Murphy (2011) indicated that the experience of flow is the reason players enjoy gaming. Taken together, this study aims to better understand the joint mediating effects of ‘a feeling of being there’ (spatial presence) on positive emotions and the effect of engaging in the challenge (flow) on positive emotions in the context of VR gaming and desktop gaming. Determining which mechanism underlies VR gaming may affect experiencing positive emotions may allow us a deeper understanding of how VR gaming affects players and how it differs from ‘traditional’ desktop gaming,
providing new opportunities for the future of gaming. By comparing the effects of VR gaming and desktop gaming, the effect of VR as a medium on the intensity of emotions can be evaluated. Looking back at the COVID-19 pandemic when people had to stay at home, VR environments proved to be a successful way to socialize with peers while exercising social distancing (Seifert & Schlomann, 2021). Gaining insight into this success can be important for game developers to uncover if the emotional rewards of VR experiences are comparable to desktop experiences. To maximize to use of VR gaming it is important to know what people think to gain from VR. Uncovering the mechanisms in VR gaming can offer insights into how they cause positive emotions. Positive emotions can offer a clearer understanding of in which situations VR gaming can be used and is chosen.
2. Theoretical Background VR gaming vs desktop gaming
Virtual reality (VR) gaming creates experiences in virtual environments in a way that is different from traditional gaming consoles. The main difference in VR is achieved through the VR headset which changes the virtual environment according to the user’s responses and movements (Riva et al., 2007). These changes are made in real-time presenting an illusion of interaction and being present in the virtual world. Compared to ‘traditional’ gaming consoles with controllers, VR gaming mode allows players to use their head rotation, eye movement, and controller movement and position to interact with the video game content (Parsons &
Rizzo, 2008). These technical differences between the two gaming modes can impact the user experience of VR and desktop games, respectively both commercial and non-commercial VR gaming have demonstrated less performance and usability among players (Tan et al., 2015;
Santos et al., 2009). As a result, these differences between VR gaming and desktop gaming may affect psychological outcomes, such as experiencing positive emotions.
The Differential Susceptibility Model (Valkenburg and Peter, 2013) is a framework that examines media effects on users. Different emotional states are considered to be the underlying mechanism of media effects and can occur during and after media exposure.
According to the basic emotion theory (Ekman, 1992; Izard, 1991), there are two approaches to emotion theory: the discrete approach to emotions and the dimensional approach to
emotions. Discrete emotions (e.g., fear, joy) can be characterized in dimensions consisting of valence (positive vs negative), arousal (high vs low), and motivational direction (approach vs avoidance) (Harmon-Jones et al., 2016). However, the properties of discrete emotions reach further than only dimensions. Cognitive evaluations, arousing states, subjective feelings, and specific action shifts are also part of discrete emotions. This study uses discrete emotion theory because of the extra properties of discrete emotions to ensure capturing emotional states as broadly as possible. Since the current study focuses on the effects of VR on positive emotions, emotional states are best suitable since it considers emotion at that exact moment, in the current contexts: immediately after exposure to VR or desktop gaming. Since the aim of the current research is the effect of gaming vs desktop gaming on positive emotions, we take a closer look at the discrete state emotions of happiness or joy and relaxation. Joy or happiness is defined by Harmon-Jones et al. (2016) as a high-approach positive emotion, meaning that people actively seek out this emotion. Relaxation is seen as a low-approach positive emotion (Harmon-Jones, 2016), meaning that people do not actively seek out this emotion but experience it as positive. Gaming has resulted in experiencing positive emotions such as relaxation and happiness (Wack & Tantleff-Dunn, 2009; Anderson et al., 2017).
Research on VR movies found that VR movies induce stronger positive and negative emotions than movies on a desktop screen (Ding et al., 2018). However, until now there is little evidence stating that VR gaming results in experiencing stronger positive emotions than
desktop gaming. One study found that VR gaming led to more intense positive emotions and higher levels of sensory and imaginative immersion (Pallavicini & Pepe, 2019). However, spatial presence was not considered as a mediator. This study will take a closer look at the specific mechanisms in the relationship between VR gaming and positive emotions. Based on the above, the following hypothesis was formulated:
H1: VR gaming will lead to experiencing a higher level of positive emotions than desktop gaming.
Mediator 1: Spatial Presence
Spatial presence is defined by Hartmann et al. (2016) as: a ‘user’s subjective feeling of
“being there” in the space displayed by a medium’ (p. 2). Spatial presence is a key concept in the context of VR research. The full 360-degree view is exclusive to VR and proved to result in increased spatial presence compared to desktop screen media (Lemmens et al., 2021;
Pallavicini et al., 2019). Spatial presence consists of two characteristics of a media structure:
vividness and interactivity (Hartmann et al., 2015). According to Steuer (1992), vividness is
“the representational richness of a mediated environment as defined by its formal features, that is, how an environment presents information to the senses” (p. 11). The vividness of a media structure depends on the number of stimuli (visual, audio, or haptic) that are received by a user’s sensory channel (Hartmann et al. 2015), more stimuli lead to a stronger vividness.
Since, VR environments present more stimuli to users through the ability of head rotations, eye movements, and moving around inside the virtual world, they have stronger vividness.
Educational VR environments lead to more spatial presence compared to viewing identical content on a desktop (Ahn et al., 2022). Based on that, it is expected that these features of VR games will lead to experiencing a higher level of spatial presence than in desktop gaming, leading to the following question:
H2: VR gaming will lead to a higher level of spatial presence than desktop gaming.
Spatial presence influences experiencing negative emotions in VR gaming (Price et al., 2011; Lemmens et al., 2021). Spatial presence relates to higher levels of self-reported fear and hostility based on the ‘realness’ of the VR session. Additionally, spatial presence has an indirect effect on the negative emotions of fear and hostility, through participants feeling present in the virtual world (Lemmens et al., 2021). The authors used heart rate variability (HRV) to indicate physical fear-related responses and self-reported questionnaires for the negative emotions. Based on that, spatial presence is expected to lead to stronger experiences of emotional states.
H3: A higher level of spatial presence will lead to experiencing more positive emotions.
Mediator 2: Flow
According to the flow theory by Csikszentmihalyi (1990), flow is a state of an optimal experience that may occur when there is a harmonious state between current skills and arisen challenges. To achieve this state, a person must only focus on the task at hand and forget about any other matters. This theory proposes that to experience flow, nine dimensions must be present: (1) challenge-skill balance, (2) clear goals, (3) unambiguous feedback, (4) action- awareness merging, (5) the concentration of the task, (6) sense of control, (7) loss of self- consciousness, (8) distorted perception of time, and (9) autotelic experience
Schubert (1998) proposed ‘embodied mental models’, meaning that individuals in virtual environments create a mental representation of the things they can do in a virtual environment. This model consists of spatial presence in the room, the experience of the own body, and opportunities the virtual environment offer (Schubert, 1998). More intuitive
feedback from the virtual world and less feedback from the real world makes it easier for a player to build such an embodied mental model. Unambiguous feedback and a sense of control are two of the nine dimensions of flow theory. So, if a virtual environment offers unambiguous feedback and sense of control through embodied mental models, the chances that flow will occur is high. Therefore, VR gaming has a higher chance to offset a higher level of flow than desktop gaming. Based on the above, the following hypothesis was proposed:
H4: VR gaming will lead to a higher level of flow than desktop gaming.
Flow has a positive effect on enjoyment in desktop gaming (Weibel and Wissmath, 2011) and thus can offer insights into why players enjoy gaming. Flow creates enjoyment in gaming through the balance between skills and challenges combined with a complete focus on completing tasks in the game (Murphy, 2011). Previous research found that flow in VR and desktop gaming leads to more positive emotions (Pallavicini & Pepe, 2019). Based on that, it is expected that a higher level of flow will be related to experiencing more positive emotions, leading to the following hypothesis:
H5: A higher level of flow will be related to higher positive emotions.
As discussed earlier, spatial presence in the room is part of Schubert’s embodied mental models (1999) and is expected to allow players to enter flow state more easily. So, a higher level of spatial presence, will make it easier to make embodied mental models and thus, easier to experience flow. Based on that, it is expected that a higher level of spatial presence will be related to a higher level of flow, leading to the following hypothesis:
H6: A higher level of spatial presence relates to a higher feeling of flow.
VR gaming has proven to evoke stronger emotional states than desktop gaming (Pallavicini & Pepe, 2019; Lemmens et al., 2021). This study will contribute to the literature
by focusing on positive emotions as the main outcome of VR gaming and evaluating two underlying mechanisms: spatial presence and flow in a double mediation model. Finally, a higher level of flow will be related to experiencing more positive emotions, which will lead to the following hypothesis:
H7: Spatial presence and flow positively mediate the effect of VR gaming on positive emotions.
The Differential Susceptibility Model (DSMM) of Valkenburg and Peter (2013) provides a framework for examing media effects. The first proposition of the DSMM model proposes different types of conditional variables called ‘differential-susceptibility variables’ that are important for predicting to what extent users may be affected by media. The current study will consider three differential-susceptibility variables: age, gender, and habitual exposure to gaming, which may help to understand to what extent individual differences in these
variables may impact the effects of VR gaming vs desktop gaming on participants.
Looking at the developmental susceptibility variable age, overall time spent gaming decreases as individuals get older (Cole & Griffits, 2007). However, older adults are less prone to cybersickness and feel more present in virtual environments than younger adults (Dilanchian et al., 2021). Therefore, the current study will control for age to assess to what extent it may affect spatial presence.
Looking at dispositional susceptibility variable gender, women spend equal time online gaming as men (Lo, Wang & Fang, 2005), but previous research reported women experiencing nausea during VR gaming experiments (Lemmens et al. 2021). To prevent the results from being affected by gender-related nausea, the current study will control for gender and disgust to test to what extent it may influence the overall outcomes.
Disgust is defined as a negative, high arousal emotion and connected to avoidance motivational direction of discrete emotions, meaning that people actively avoid this emotion.
The disgust scale was used as a control variable due to previous VR research reporting that participants can experience nausea caused by the VR headset (Lemmens et al., 2021).
Habitual exposure to gaming could influence the outcomes through more frequent players having a higher level of skills. Flow occurs when the player’s skill level and challenges at hand are in balance (Csikszentmihalyi, 1990). People with a high level of habitual video gaming might have difficulties experiencing flow because their level of gaming skills could be too high for the encountered challenges in the selected video game.
On the other hand, people with no habitual gaming experience may also have problems feeling flow, since their unfamiliarity with the controls might add an extra challenge to the video game. Therefore, the current study will control for habitual exposure to gaming to evaluate to what extent it may affect the level of flow experienced by participants.
Figure 1. Conceptual model
The design of this study was a two-group experimental design. The participants were randomly assigned either to the experimental condition (VR) or the control condition (desktop) to ensure that the differences in the results are a casual effect of the experimental
manipulation. The game mode factor was a between-subjects variable (two levels: VR game vs desktop game). Spatial presence and flow were used as continuous mediators of the relationship between game mode and positive emotions.
A total of N = 68 participants (M age = 21.0, SD = 0.43) were recruited and played the
adventure puzzle game XING: The Land Beyond in VR or on a monitor. All participants were university students, and the majority of the participants were female (n = 52; 76.5%). The sample consisted of 42 participants who had a European nationality, 11 participants who had an Asian nationality, and 8 participants who had American nationality. The majority of the participants (80.6%) filled out high school as their highest completed education level, 6.5%
filled out higher vocational education as their highest completed education, and 12.9% filled out a bachelor’s degree as their highest completed education. According to Fritz &
MacKinnon (2007), 30 participants per condition is sufficient for mediation analysis but due to previous reports of participant mortality in VR research due to feelings of nausea
(Lemmens et al., 2021), the sample size was aimed at 70 participants. There were two criteria for participant inclusion: (1) Participants were 18 years or older and (2) had no history of epilepsy due to the video game content. All participants consented before the experiment started. The participants were recruited through the UvA participant tool Communication Science and word-of-mouth dissemination. UvA Communication Science participants were rewarded with 2 Research Credit points and other participants were rewarded with a Bol.com gift card worth 10 euros.
Every participant was randomly assigned to the experimental group who played XING: The Land Beyond (White Lotus Interactive, 2017) in VR or to the control group who played XING: The Land Beyond on PlayStation 4 on the desktop monitor. For the VR condition,
participants used the PSVR headset allowing for a 360-degree view. In the control condition, participants played the game on a flatscreen monitor. In both conditions, the participants were seated, wore headphones for audio, and used the Ps4 DualShock controller to interact with the game environment. Before the experiment started, all participants received a brief explanation about the DualShock controls for movement and interaction in the gaming environment. Before playing the game, participants were warned about the possibility of experiencing nausea in both conditions. The experiment consisted of three phases: (1) a pre- test questionnaire in Qualtrics about demographics and previous video game experience; (2) playing XING: The Land Beyond for 25 minutes and (3) a post-test questionnaire in Qualtrics including questions about spatial presence, flow, and positive emotions. After these 25
minutes of gaming, participants were notified that the time was finished and informed to continue the questionnaire on the laptop. After completing this questionnaire, participants were thanked, debriefed, and rewarded.
Figure 2. Picture of the experimental setting
XING: The Land Beyond (White Lotus Interactive, 2017) was used as the stimulus game for this experiment. XING: The Land Beyond is an exploration video game set in the afterlife, the objective is to solve logical puzzles with the help of the game environment. It has a built-in VR function, which made it possible to create a VR condition and desktop screen condition with identical video game content. For the manipulation, participants played XING: The Land Beyond for 25 minutes without the introductory cutscene. Therefore, the game started immediately, and players could start exploring right away. The 25-minute time frame was selected since the earlier studies (Bisson et al., 2012; Tobin et al., 2010, Rutrecht et al., 2021) discovered that video game players often overestimated the duration of their
playtime during an ‘adaptation period’. The adaption period entails that, players need time to become fully immersed in the video game (Tobin et al., 2010). However, after this period has passed, participants are more likely to underestimate their playtime (Tobin et al., 2010). This can be explained that players need time to get into a flow state (Rutrecht et al., 2021).
Therefore, in this study, a 25-minute game session was selected to create an opportunity for players to achieve flow state.
Figure 3. (A screenshot of XING: The Land Beyond, Steam, 2017)
For the manipulation check, an adapted 5-item version of Engelhardt et al. (2015) was used. The original scale measured violence; it was adapted to measure the effect of the game experience. All items on both scales except the frustration item were measured on a 7-point Likert scale, 1 = strongly disagree; 7 = strongly agree. The items sample included ‘I felt excited while playing the video game.’, ‘I felt engaged while playing the video game.’, ‘I found the game I played to be interesting’ and ‘I found the game I played to be challenging.’.
The frustration item ‘To what extent were you frustrated by the video game you played?’ was measured on a 7-point scale ranging from 1 = not at all; 4 = moderately; 7 = extremely.
To measure positive emotions the Discrete Emotions Questionnaire (DEQ) of Harmon-Jones et al. (2016) was applied. The DEQ measures subjective experiences of discrete emotions and consists of eight unique self-reported emotional states: (1) desire, (2) happiness, (3) anger, (4) disgust, (5) anxiety, (6) fear, (7) sadness, and (8) relaxation. All 8 items were answered on a 7-point Likert scale ranging from 1 (Not at all) to 7 (An extreme amount). However, given the focus of the current study on positive emotions, only two subscales were used: happiness (α = 0.96) and relaxation (α = 0.84) and both scales were reliable. Participants were asked:
‘While playing the game, to what extent did you experience the following emotions?:. The happiness sub-scale (α = 0.96) was reliable, and the items included ‘Enjoyment’, ‘Happy’,
‘Liking’, and ‘Satisfaction’. The relaxation sub-scale (α = 0.84) also measured positive emotions and the items included ‘Chilled out’, ‘Easygoing’, ‘Calm’, and ‘Relaxation’. To measure overall positive emotions, the happiness sub-scale (4 items) and the relaxation sub- scale (4 items) were combined into one continuous positive emotions scale (α = 0.93) and the scale was reliable.
An adapted version of Hartmann et al.’s (2016) spatial presence short scale was used.
All items were answered on a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). The items included ‘I felt like I was actually there in the environment of the presentation.’, ‘It seemed as though I actually took part in the action of the presentation.’, ‘It was as though my true location had shifted into the environment in the presentation.’, ‘I felt as though I was physically present in the environment of the presentation.’, ‘The objects in the presentation gave me the feeling that I could do things with them.’, ‘I had the impression that I could be active in the environment of the presentation.’, ‘I felt like I could move around among the objects in the presentation.’, and ‘It seemed to me that I could do whatever I
wanted in the environment of the presentation.’. Higher scores on the scale indicate higher feelings of spatial presence and the scale was reliable (α = 0.91).
To measure flow, an adapted version of the Short Flow Items scale (Martin &
Jackson, 2008) consisting of 9 items was used after adapting it to the video game context by changing the questions to include games. The adapted flow scale measured the level of flow the player experienced during the gameplay. It consists of nine items measured on a Likert 5- point scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). The items included ‘I felt I was competent enough to meet the high demands of the game session.’, ‘I did things spontaneously and automatically without having to think in the game session.’, ‘I had a strong sense of what I wanted to do in the game session.’, ‘I had a good idea while I was gaming about how well I was doing.’, ‘I was completely focused on the game task at hand.’,
‘I had a feeling of total control in the game session.’, ‘I was not worried about what others might think of me during the game session.’, ‘The way time passed in the game session seemed to be different from normal.’, and ‘The experience of the game session was extremely rewarding.’. The flow scale was reliable, α = 0.80.
Habitual video gaming was a dichotomous control variable and was measured with a scale developed by Dobrowolski et al. (2015). Participants were asked: (1) whether they identify themself as gamers, (2) how many hours/week did they play in the past 6 months, (3) to name favorite game genres, (4) to name up to three favorite game titles, (5) select on which device they usually play: PlayStation / Nintendo Switch / PC / Xbox / VR / Mobile phone / other. If more than 20 participants played 6 or fewer hours/week, a dichotomous variable would be created, differentiating between habitual gaming and non-habitual gaming. For the dichotomous variable, participants who played 7 hours or more per week would be coded as habitual video gamers (1), and those who played 6 hours/week or less were coded as non- habitual video gamers (0).
The disgust sub-scale of the DEQ questionnaire (Harmon-Jones et al., 2016) was used (α = 0.76, M = 2.15, SD = 1.27) to control for feelings of nausea that could be experienced, especially in the VR game mode condition. The instruction was ‘while playing the game to what extent did you experience these emotions?’. The items included ‘Revulsion’, ‘Grossed out’, ‘Sickened’, and, ‘Nausea’. All 4 items were answered on a 7-point Likert scale ranging from 1 (Not at all) to 7 (An extreme amount).
4. Results Preliminary Results
In the VR condition, four female participants dropped out due to feelings of nausea. Two participants in the VR condition dropped out due to technical issues e.g., wrong VR settings.
One participant from the desktop condition was excluded due to audio-technical issues.
Therefore, their data were excluded from the analyses. In the end, N = 62 adults were included: n = 31 participants in the VR condition and n = 31 participants in the desktop condition, M age = 21.06 and SD = 1.95.
For the manipulation check, there were no significant differences between the VR condition and desktop conditions (see details in Table 1). These results showed that the manipulation was successful. Thus, it was confirmed that participants experienced the video game content in a comparable way unrelated to their assigned experiment condition.
However, participants in the VR condition (M = 2.75, SD = 1.36) scored significantly higher on the disgust scale than participants in the desktop condition (M = 1.43, SD = 0.64), t (42) = -4.89, p < .001. Therefore, to account for the differences in experiencing disgust between the two conditions, disgust was included as a covariate in the main analysis to control for the level of disgust in the analyses.
Results of the Independent Samples t-test for the manipulation check
VR M (SD)
desktop M (SD)
df t p
Excitement 4.74 (2.02) 4.42 (1.50) 60 - 0.72 .175
Engaged 5.32 (1.62) 5.13 (1.52) 60 - 0.49 .630
Interesting 5.03 (1.87) 5.00 (1.48) 60 - 0.08 .940
Challenging 5.03 (1.43) 4.74 (1.64) 60 - 0.79 .431
Frustrated 3.29 (1.70) 2.94 (1.41) 60 - 0.90 .374
Disgust 2.75 (1.36) 1.43 (0.64) 42 - 4.89 < .001
For the habitual gaming experience, participants played video games on average 3.35 hours (SD = 5.46) per week in the last six months. The minimum was 0 hours per week and the maximum was 30 hours per week. The habitual gaming experience was controlled for if more than 20 participants played video games for 6 hours or less per week for the last 6 months (Dobrowolski et al., 2015). The results showed that 59 participants fell into the non- habitual gaming group. Thus, a dichotomous variable of habitual gaming was created with a majority (86.6%) of 59 non-habitual gamers and 9 habitual gamers. Lastly, most of the participants did not identify as a gamer (76.5%) and less than half of them had no previous experience with VR (40%).
Main variables Table 2
Results of the Independent Samples t-test for the main variables
VR M (SD)
desktop M (SD)
Total M (SD)
df t p
3.54 (0.72) 2.79 (0.88) 3.16 (0.88) 60 0.40 .690
Flow 3.25 (0.58) 3.32 (0.74) 3.29 (0.66) 60 -3.66 .001
4.01 (1.46) 4.29 (1.34) 4.15 (1.40) 60 0.79 .431
As indicated in the comparison between the conditions (see Table 2), an independent sample t-test showed that the differences between the VR condition (M = 3.54, SD = 0.72), and the desktop condition (M = 2.79, SD = 0.88) were not significantly different for spatial presence. The differences between the VR condition (M = 3.25, SD = 0.58) and the desktop condition (M = 3.32, SD = 3.32) were significantly different for flow, t (60) = -3.66, p = .001.
Participants in the desktop condition experienced significantly more flow than participants in the VR condition. Moreover, the differences between the VR condition (M = 4.01, SD = 1.46) and the desktop (M = 4.29, SD = 1.34) condition were significantly different for positive emotions.
To evaluate the hypotheses, PROCESS Macro model 6 with game mode as a predictor, positive emotions as the outcome variable, spatial presence as a mediator 1, and flow as a mediator 2 was used. The confidence interval was 95% and the indirect effects were assessed by adding 5000 bootstrapping samples.
The first model with spatial presence as the dependent variable was significant, F (60)
= 13.42, p < .001, R = 0.43 and R2 = 0.18. Thus, 18% of the variance in spatial presence can
be explained through this model. The second model with positive emotions as the dependent variable was significant, F (58) = 12.23, p < .001, R = 0.62 and R2 = 0.39. Thus, 39% of the variance in spatial presence can be explained through this model. The third model with flow as the dependent variable was significant, F (59) = 19.27, p < .001, R = 0.63 and R2 = 0.40.
Thus, 40% of the variance in flow can be explained through this model.
The effect of game mode (VR vs desktop) on positive emotions
H1 expected that VR gaming increased positive emotions as compared to desktop gaming.
Results indicated that this effect was not significant: b* = -0.09, SE = 0.34, t (58) = -0.37, p = .715, CI [-0.80, 0.56]. These results did not support the H1.
The effect of game mode on spatial presence
H2 expected an effect of game mode on spatial presence. The results indicated a significant effect of VR game mode on spatial presence: b* = 0.85, SE = 0.20, t (60) = 3.67, p < .001, CI [0.34,1.16]. VR gaming had a positive effect on spatial presence, therefore people in the VR mode experienced a higher level of spatial presence and supported the H2.
The effect of spatial presence on positive emotions
H3 expected that spatial presence increased experiencing positive emotions. The results indicated no effect of spatial presence on increasing positive emotions: b* = -0.06, SE = 0.23, t (58) = -0.38, p = .707, CI [-0.55, 0.37]. Thus, the H3 was not supported.
The effect of game mode on flow
H4 expected that game mode had a positive effect on the level of flow. The results indicated a significant negative relationship: b* = -0.69, SE = 0.15, t (59) = -3.12, p = .003, CI [-
0.75,0.16], suggesting that VR gaming led to a lower level of flow than desktop gaming. The results showed the opposite effect of the proposed H4 thus, the hypothesis was not supported.
The effect of flow on positive emotions
H5 expected that a higher level of flow led to more positive emotions. The results indicated a significant positive relationship: b* = 0.64, SE = 0.28, t (58) = 4.88, p < .001, CI [0.80, 1.91].
Thus, experiencing a higher level of flow led to experiencing more positive emotions.
Therefore, the H5 was supported.
The effect of spatial presence on flow
H6 expected that a higher level of spatial presence led to a higher level of flow. The results indicated a significant positive relationship: b* = 0.69, SE = 0.08, t (59) = 6.19, p < .001, CI [0.35, 0.69]. Thus, experiencing a higher level of spatial presence led to experiencing a higher level of flow. Therefore, the H6 was supported.
The effect of game mode on positive emotions mediated through spatial presence and flow
H7 expected that spatial presence and flow function mediated the relationship between exposure to VR games and positive emotions. The results indicated a positive indirect effect of spatial presence and flow on positive emotions: partially standardized b* = 0.38, SE = 0.20, CI [0.20, .99]. Thus, spatial presence and flow did indeed lead to more positive emotions while playing VR games, H7 was supported.
Figure 4. Summary of the double mediation results (PROCESS Macro Model 6), presenting the results
After adding the four covariates; disgust, gender, age, and habitual exposure to the double mediation model did not change the main results (see appendix A), the double mediation (H7) was still significant. However, the results indicated a significant negative indirect effect of disgust on flow: b = -0.15, SE = 0.06, t (55) = -2.39, p = .002, CI [-0.28, -0.24]. Thus, a higher feeling of disgust led to a lower level of flow. For the rest of the outcomes, there were no significant relationships. Therefore, H7 was still supported.
Disgust (M = 2.15, SD = 1.27) as the only covariate in the double mediation model changed the results for the relationship between the game mode and flow. When controlled for disgust, the effect of game mode on flow changed and became nonsignificant: b* = -0.32, SE = 0.17, t (58) = -1.26, p = 0.21, CI [-0.55, 0.13]. This indicated that there was no effect of game mode on the level of flow, discarding H4. Furthermore, disgust had a significant negative effect on flow: b* = -0.31, SE = 0.06, t (58) = -2.62, p = .011, CI [-0.29, -0.04].
Therefore, feelings of disgust were the reason that VR participants experienced a lower level of flow. Thus, the game mode did not have any effect on flow. Furthermore, H7 was still supported.
Gender as a only covariate showed a significant negative effect on flow: b* = -0.26, SE = 0.15, t (58) = - 2.59, p = .012, CI [-0.69, -0.09]. This showed that females were less likely to experience flow than males. When age and habitual exposure to gaming were added separately to the double mediation model, there were no significant changes in the main results. H7 was supported in all separate covariate models.
This research aimed to identify if VR gaming had an effect on positive emotions, spatial presence, and flow. Contrary to expectations, the results showed that VR gaming did not directly influence positive emotions. VR gaming did, however, affect spatial presence, in line with our expectations. In turn, spatial presence affected positive emotions. VR gaming led to a higher level of spatial presence and a higher level of spatial presence led to a higher level of flow. The effect of VR gaming on positive emotions was dependent on serial mediation through spatial presence and flow. Therefore, it can be concluded that spatial presence and flow are two of the underlying mechanisms in the relationship between VR gaming and positive emotions. Thus, key factors to consider for game developers when designing video games for their audience.
This study proved that gaming can lead to stronger positive emotions in VR, additionally to VR in cinema (Ding et al., 2018) and VR in education (Ahn et al., 2022). VR gaming is more pleasurable than desktop gaming through the increase in positive emotional states (Herrero et al., 2014). Furthermore, this study adds evidence to the limited academic field (Pallavicini &
Pepe, 2019) on the effect of VR gaming on positive emotions. This study additionally proved that flow and spatial presence increased positive emotions in VR gaming and not only
desktop gaming (Weibel & Wissmath, 2011). The increased spatial presence in VR gaming allows the medium to create feelings of flow that lead to more positive emotions. In line with
the results found about spatial presence affecting emotions in VR gaming (Price et al., 2011;
Lemmens et al., 2021), this research adds by confirming this also holds true for positive emotions, not just negative emotions. Spatial presence is one of the mechanisms in VR gaming causing stronger emotional experiences. Investigating the relationship between flow and positive emotions allowed to take a closer look at how these emotions generate from the action of VR gaming. This study proved that VR gaming generates stronger positive
emotions for puzzle games, adding to the literature that focused on race games (Pallavicini &
Pepe, 2019). In line with Weibel and Wissmath (2011), flow proved to influence positive emotions in gaming and this study provides evidence for VR as well. Nausea remains a problem for VR gaming (Lemmens et al., 2021) by preventing players from experiencing flow. As VR headsets develop more in the future it is expected that creating embodied mental models Schubert (1998) becomes even easier, granting more opportunities for flow in VR experiences.
Limitations and further directions
This research has provided evidence for females experience more cybersickness than males in VR gaming, in line with expectations (Lemmens et al, 2021) but the influence of gender on gaming affects flow experience in video games as well. Moreover, the stronger emotional experience of VR gaming can be the reason that players prefer VR gaming over desktop gaming in the future. The dispositional susceptibility of the DSMM (Valkenburg and Peter, 2013) anticipated that gender affected the effect of VR gaming. Therefore, game developers and scholars should examine the underlying reason females experience gaming in a different manner than men, especially zooming in on feelings of flow. The technical equipment used in this experiment was the PlayStation VR (PSVR) headset. The PSVR is set to a fixed
interpupillary distance (IPD) and is unable to adjust the IPD to accommodate different
players. Stanney et al. (2020) state that cybersickness is dependent on the match of the IPD of
the user and that specifically, females have a harder time getting a fit. The authors
recommend creating a wider IPD adjustable range to lower cybersickness, specifically for women. Therefore, future research should use VR headsets that offer adjustable IPD ranges such as the Oculus Quest 2. Additionally, game developers should consider the biological differences between males and females and design products suitable for all genders. The sample was not representable for the general public, due to the sample consisting solely of bachelor or master university students, leading to the education level being too high to represent the general population (OECD, 2019). Furthermore, since the average age of participants was close-knitted, it was not possible to examine whether nausea experienced in the VR condition (Dilanchian et al., 2021) was influenced by age. To better understand the implications of these results, future studies should recruit a more balanced sample in terms of gender and age, especially with previous research on cybersickness on age and gender in mind.
In sum, this study adds to the academic field of VR gaming as a medium that increases feelings of spatial presence and feelings of flow amongst players. Spatial presence mediates the feeling of flow, causing players to have a more optimal experience in the VR world. In turn, flow mediates the experience of positive emotions, which leads to more happiness and relaxation in VR gaming. Thus, VR games create an opportunity for players to experience the gaming world in a new and emotively powerful way.
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Appendix Appendix A Exploratory Results
Run MATRIX procedure:
***************** PROCESS Procedure for SPSS Version 4.0 *****************
Written by Andrew F. Hayes, Ph.D. www.afhayes.com
Documentation available in Hayes (2022). www.guilford.com/p/hayes3
Model : 6 Y : poem_m
X : gamemode M1 : pres_m M2 : flow_m
Sample Size: 62
R R-sq MSE F df1 df2 p
,4431 ,1964 ,6497 7,2083 2,0000 59,0000 ,0016
coeff se t p LLCI ULCI
constant 2,7190 ,1597 17,0260 ,0000 2,3994 3,0385 gamemode ,7981 ,2103 3,7946 ,0004 ,3772 1,2189 habigam ,2981 ,2985 ,9986 ,3221 -,2992 ,8955
coeff gamemode ,9025 habigam ,1197
R R-sq MSE F df1 df2 p
,6527 ,4260 ,2657 14,3465 3,0000 58,0000 ,0000
coeff se t p LLCI ULCI
constant 1,8500 ,2484 7,4487 ,0000 1,3528 2,3471 gamemode -,3890 ,1500 -2,5930 ,0120 -,6893 -,0887 pres_m ,5010 ,0833 6,0170 ,0000 ,3343 ,6677 habigam ,3398 ,1925 1,7651 ,0828 -,0456 ,7252
Standardized coefficients coeff
gamemode -,5864 pres_m ,6677 habigam ,1819
R R-sq MSE F df1 df2 p
,6298 ,3967 1,2581 9,3687 4,0000 57,0000 ,0000
coeff se t p LLCI ULCI
constant -,0562 ,7559 -,0743 ,9410 -1,5698 1,4574 gamemode -,1786 ,3448 -,5179 ,6065 -,8691 ,5119 pres_m -,0960 ,2309 -,4156 ,6792 -,5583 ,3664 flow_m 1,4172 ,2857 4,9604 ,0000 ,8451 1,9893 habigam -,4019 ,4300 -,9347 ,3539 -1,2630 ,4592
Standardized coefficients coeff
gamemode -,1280 pres_m -,0608 flow_m ,6736 habigam -,1023
************************** TOTAL EFFECT MODEL
R R-sq MSE F df1 df2 p
,1209 ,0146 1,9851 ,4378 2,0000 59,0000 ,6475
coeff se t p LLCI ULCI
constant 4,2350 ,2791 15,1718 ,0000 3,6765 4,7936 gamemode -,2399 ,3676 -,6525 ,5166 -,9755 ,4957 habigam ,2627 ,5218 ,5035 ,6165 -,7814 1,3069
Standardized coefficients coeff
gamemode -,1719 habigam ,0668
************** TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y
Total effect of X on Y
Effect se t p LLCI ULCI c_ps -,2399 ,3676 -,6525 ,5166 -,9755 ,4957 -,1719
Direct effect of X on Y
Effect se t p LLCI ULCI c'_ps -,1786 ,3448 -,5179 ,6065 -,8691 ,5119 -,1280
Indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI TOTAL -,0613 ,3283 -,7334 ,5618 Ind1 -,0766 ,2306 -,5613 ,3776 Ind2 -,5513 ,2401 -1,0956 -,1647 Ind3 ,5666 ,2203 ,2146 1,0701 (C1) ,4747 ,2651 -,0344 1,0117 (C2) -,6432 ,3848 -1,4931 -,0267 (C3) -1,1179 ,3899 -2,0153 -,4871
Partially standardized indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI TOTAL -,0439 ,2360 -,5117 ,4171 Ind1 -,0549 ,1666 -,3943 ,2820 Ind2 -,3950 ,1641 -,7573 -,1251 Ind3 ,4059 ,1535 ,1629 ,7610 (C1) ,3401 ,1885 -,0242 ,7138 (C2) -,4608 ,2710 -1,0709 -,0201 (C3) -,8009 ,2645 -1,4160 -,3704
Specific indirect effect contrast definition(s):
(C1) Ind1 minus Ind2 (C2) Ind1 minus Ind3 (C3) Ind2 minus Ind3
Indirect effect key:
Ind1 gamemode -> pres_m -> poem_m Ind2 gamemode -> flow_m -> poem_m
Ind3 gamemode -> pres_m -> flow_m -> poem_m
*********************** ANALYSIS NOTES AND ERRORS
Level of confidence for all confidence intervals in output:
Number of bootstrap samples for percentile bootstrap confidence intervals:
NOTE: Standardized coefficients for dichotomous or multicategorical X are in partially standardized form.
--- END MATRIX ---