Time Compression in Virtual Reality

Abstract

Virtual-reality (VR) users and developers have informally reported that time seems to pass more quickly while playing games in VR. We refer to this phenomenon as time compression : a longer real duration is compressed into a shorter perceived experience. To investigate this effect, we created two versions of a labyrinth-like game. The versions are identical in their content and mode of control but differ in their display type: one was designed to be played in VR, and the other on a conventional monitor (CM). Participants were asked to estimate time prospectively using an interval production method. Participants played each version of the game for a perceived five-minute interval, and the actual durations of the intervals they produced were compared between display conditions. We found that in the first block, participants in the VR condition played for an average of 72.6 more seconds than participants in the CM condition before feeling that five minutes had passed. This amounts to perceived five-minute intervals in VR containing 28.5% more actual time than perceived five-minute intervals in CM. However, the effect appeared to be reversed in the second block when participants switched display conditions, suggesting large novelty and anchoring effects, and demonstrating the importance of using between-subjects designs in interval production experiments. Overall, our results suggest that VR displays do produce a significant time compression effect. We discuss a VR-induced reduction in bodily awareness as a potential explanation for how this effect is mediated and outline some implications and suggestions for follow-up experiments.

Full text

* To whom correspondence should be addressed. E-mail: gmullen@ucsc.edu
** ORCID: ---
*** ORCID: ---
Time Compression in Virtual Reality
Grayson Mullen*,** and Nicolas Davidenko***
Department of Psychology, University of California, Santa Cruz, CA , USA
Received  August ; accepted  March 
Abstract
Virtual-reality (VR) users and developers have informally reported that time seems to pass more
quickly while playing games in VR. We refer to this phenomenon astime compression: a longer
real duration is compressed into a shorter perceived experience. To investigate this efect, we cre-
ated two versions of a labyrinth-like game. The versions are identical in their content and mode
of control but difer in their display type: one was designed to be played in VR, and the other on a
conventional monitor (CM).Participants were asked to estimate time prospectively using an inter-
val production method. Participants played each version of the game for a perceived ve-minute
interval, and the actual durations of the intervals they produced were compared between display
conditions.We found that in the rst block, participants in the VR condition played for an average
of . more seconds than participants in the CM condition before feeling that ve minutes had
passed.This amounts to perceived ve-minute intervals in VR containing .% more actual time
than perceived ve-minute intervals in CM.However, the efect appeared to be reversed in the sec-
ond block when participants switched display conditions, suggestinglarge novelty and anchoring
efects, and demonstrating the importance of using between-subjects designs in interval production
experiments.Overall, our results suggest that VR displays do produce a signicant time compression
efect. We discuss a VR-induced reduction in bodily awareness as a potential explanation for how
this efect is mediated and outline some implications and suggestions for follow-up experiments.
Keywords
Virtual reality, bodily awareness, interoception, time compression, prospective time estimation,
presence, immersion
G. Mullen and N. Davidenko
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© Grayson Mullen and Nicolas Davidenko,  DOI: ./-bja
This is an open access article distributed under the terms of the CC BY . license.
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1. Introduction
Virtual-reality (VR) head-mounted displays (HMDs) take up the user’s entire eld
of view, replacing all of their real-world visual cues with a contrived virtual world.
This imposes unique conditions on human vision and on all other brain functions
that make use of visual information. The consequences have mostly been studied
in terms of presence, or the feeling of being inside the virtual scene presented on
the HMD rather than in the real world (see Heeter,  for a more encompassing
and widely used denition of presence). Because the virtual scene can be designed
to look like anything, VR can produce unique psychological efects by placing users
in situations that rarely (or never) occur naturally. For example, it can present
visual stimuli that conict with the users’ vestibular cues, causing cybersickness
(Davis et al., ). VR experiences have also been intentionally used to reduce
pain in burn patients (Hofman et al., ), to elicit anxiety or relaxation (Riva
et al., ), and even to afect self-esteem and paranoia by manipulating the
height of the user’s perspective relative to the virtual scene (Freeman et al., ).
One unintentional efect, which has been anecdotally reported by VR users and
developers, is a time compression phenomenon wherein a larger real duration is
compressed into a shorter perceived experience. At a  gaming conference,
Hilmar Veigar (of CCG Games) said, “You think you’ve played for  minutes and
then you go out and it’s like, ‘Wait, I spent an hour in there?’ There’s a concept of, I
don’t know, VR time” (Miller, ). Palmer Luckey (founder of Oculus) suggested
that the efect could be a result of not having access to real-world environmental
cues, like the position of the sun. Distorted time perception has been observed as
an efect of conventional gaming (Nuyens et al., ), but the inuence of VR on
time perception has been studied relatively less.
One notable study (Schneider et al., ) successfully used VR experiences
to shorten perceived durations during chemotherapy and found individual dif-
ferences in time compression efects related to diagnosis, gender and anxiety. It is
not clear, though, whether a non-VR version of the same experience would have
resulted in a similar distortion of time perception. Only a few studies have directly
compared time estimation processes between a VR experience and a non-VR
counterpart, and none so far have found signicant diferences.
Bansal et al. () examined the inuence of a novel modication of a VR
game (which coupled the ow of time to the speed of players’ body movements)
on participants’ performance on subsequent time estimation tasks. Compared
to control groups, participants who played the modied game made shorter
estimates of brief (s and shorter) intervals, but only on estimation tasks that
involved continuous movement. No signicant diference in time perception was
found between participants who played an unmodied (normal-time) version of
the VR game and those who played a non-VR game. These results indicate that VR
alone may not recalibrate temporal perception, but that a specically tailored VR
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experience may induce such an efect. Because all the time estimation tasks were
performed outside of VR, these results do not provide an answer to the question
of whether time perception is distorted during VR use.
Schatzschneider et al. () investigated how time estimation was afected by
display type (VR/non-VR) and cognitive load. The researchers found no signicant
diference in time estimation between the display conditions, but the study used a
within-subjects design and all participants experienced the non-VR condition rst
and the VR condition second. Completing the non-VR condition rst may have
anchored participants’ time estimates in the subsequent VR condition. Thus, it is
possible that the lack of counterbalancing in Schatzschneider et al. () may
have obscured an efect of display type. Another study (van der Ham et al., )
also found no diference in time estimates between VR and non-VR displays, but
used a retrospective time estimation paradigm.
According to Block and Zakay (), retrospective and prospective time esti-
mates depend on diferent processes. Retrospective estimates are made when par-
ticipants are unaware that they will be asked to estimate a duration until after the
interval has ended. These estimates are based only on information that is stored
in memory. Factors that have been found to afect retrospective time estimates
are mostly related to stimulus complexity and contextual changes (more com-
plex information and more changes are associated with longer retrospective esti-
mates). Because they rely on memory, retrospective time estimates are afected
by cognitive load only indirectly, when information relevant to cognitive load is
stored in memory.
In contrast, prospective estimates are made by participants who are aware dur-
ing the interval that they will be asked to estimate its duration. The most promi-
nent model to illustrate the processes underlying prospective time estimation is
Zakay and Block’s () attentional-gate model of prospective time estimation
(but see also Grondin, ; Ivry & Schlerf, ; and Wittmann,  for reviews
of alternate models of time perception). The rst component of this abstract
model is a pacemaker (which can be thought of as an internal metronome) that
generates pulses at a rate that scales with the estimator’s arousal. Before the pulses
can be counted, they are modulated by an attentional gate, which is open to a vari-
able degree depending on the amount of attentional resources allocated to track-
ing time. When attentional resources are consumed by a demanding task, the gate
becomes narrower (i.e., fewer resources are available to attend to time), and fewer
pulses are able to pass.
The pulses that pass the attentional gate are counted by an accumulator, and
the resulting sum is used as the basis for an estimate of the interval’s duration.
The larger the count, the more time the estimator reports has passed. This means
that time seems to pass more quickly (i.e., it becomes compressed) when atten-
tional demands are high, and it seems to pass more slowly (i.e., it dilates) when
attentional demands are low. The attentional-gate model is supported by the
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preponderance of attention-related manipulations that have been found to sig-
nicantly afect prospective estimates, but not retrospective estimates (Block &
Zakay, ). Thus, whereas prospective estimates are afected by cognitive load,
retrospective estimates are more afected by contextual changes and other mem-
ory-related factors.
The current study is the rst to investigate the efect of VR HMDs on time
perception using a prospective time estimation paradigm and counterbalanced
display conditions. We chose a prospective time estimation paradigm in order to
measure the experience of VR rather than the memory of it (Block & Zakay, ),
and also to obtain results that are relevant to intentional time management while
playing VR games. We also used an interval production method of time estimation
(Zakay, ), in which the research assistant species a duration (ve minutes,
in our case) and the participant starts and ends an interval that they feel matches
that duration. This method is less susceptible to rounding biases than methods
that ask the participant to report the number of seconds or minutes an interval
lasted. In our study, every participant attempts to produce a ve-minute interval,
and we use the actual durations of the intervals they produce as our main depen-
dent variable.
..Hypotheses
First, we predict that intervals produced while playing a VR game will be longer
than those produced while playing an equivalent game displayed on a conven-
tional monitor (CM). This hypothesis is based on the anecdotal reports of a time
compression efect in VR, and is motivated by past studies which have probed the
relationship between time perception and VR but failed to nd evidence of this
efect. Based on Block and Zakay’s () comparison of time estimation meth-
ods, we expect an interval production method to yield evidence of a compression
efect in VR that has not been directly revealed by other methods.
Second, we predict that VR interval durations will be more variable across par-
ticipants than CM interval durations. Higher variability is naturally expected if
VR interval durations are longer, assuming that errors are proportional to the size
of the estimate. Additionally, we predict that variability may be further increased
by uncertainty in time perception among participants in VR. If VR interferes with
normal time perception, participants may be less condent in their ability to track
the passage of time, and produce a wider range of interval durations.
2. Methods
.Participants
Forty-one undergraduate students participated for course credit. Two of them
produced extreme outlier responses (their intervals in the VR condition were
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more than three standard deviations above the mean), so our nal analysis
includes data from  participants ( female and  male, ages –, M=.,
SD=.).The UC Santa Cruz IRB approved the study and participants provided
informed consent.
.Materials
In both conditions, participants played a D labyrinth-like game designed in
Unity. Each level consisted of a oating maze inside an otherwise empty room
with textured walls and oors (see Fig. ). The lighting and object textures did
not change between levels, conditions, or maze sets, and there was no representa-
tion of the user’s body. The maze was positioned in front of and below the virtual
camera to allow participants to see into the maze from above. Each maze con-
tained a ball and a glowing yellow cube representing a goal, as well as walls and
holes in the oor. Participants were directed to guide the ball to the goal by tilting
the maze. Each version of the game included one of two maze sets (designed to
be equally complex and dicult) so that participants did not repeat any levels
between the two conditions. Each version included one practice level followed
by up to  timed levels, which became increasingly dicult to complete as the
mazes became larger and more complex (to simulate the general sense of pro-
gression in video games). Letting the ball fall through a hole in the maze would
restart the current level, while getting the ball to reach the goal would start the
next level. Above the maze in the timed levels, white text reading, “When you
think ve minutes have passed, press the right bumper and trigger at the same
time” continuously faded in and out on an -s cycle to remind participants of the
interval production task.
Figure 1.The sixth level of maze set A as viewed by participants in both the virtual reality (VR) and
conventional monitor (CM) condition. The superimposed yellow line (not shown to participants)
indicates a path to the goal.
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We decided it was important to include this reminder because when using
an interval production method, the interval does not end until the participant
chooses to end it. If a participant forgets that they were asked to keep track of time,
they could produce exceedingly long intervals that are not accurately descriptive
of their perception of time. Although the periodic fading of the reminder may
have served as a temporal cue to make time perception more accurate, we do not
expect it to have confounded our results because it was presented the same way in
the VR and CM conditions of the game.
Participants used an Xbox  controller (Microsoft Corporation; Redmond,
WA, USA) to manipulate the maze. They could tilt it in eight directions by moving
the left joystick and could return it to its original position by holding any of the
colored buttons (A, B, X, or Y). The right trigger and bumper (buttons at the back
of the controller) were pressed simultaneously to end the practice level, and later
to indicate the end the perceived -min interval.
In the VR condition, participants wore an Oculus Rift CV HMD (Oculus VR;
Menlo Park, CA, USA) with head-tracking enabled to show a stable D environ-
ment. In the CM condition, participants viewed the game on a -inch Dell moni-
tor with a  ×  pixel resolution and a Hz refresh rate. Participants in
the CM condition were seated approximately cm away from the monitor. At
this distance, the maze subtended approximately degrees by degrees of
visual angle. Participants in the VR condition saw the maze from a virtual camera
that was positioned similarly with respect to the maze, but the maze subtended
a slightly larger visual angle (approximately degrees by degrees). However,
participants were allowed to move freely during the game in both conditions, so
the visual angle of the maze varied considerably across participants and across
maze levels. Other than these diferences between displays, the game was played
on the same computer hardware between conditions.
After completing both conditions, participants lled out a questionnaire that
asked about the diculty of tracking time and of playing the game, their con-
dence in their ability to estimate time, previous experience with VR and video
games, and included  Likert-scale items about immersion (e.g., “I felt detached
from the outside world”). The purpose of this immersion scale was to measure
whether participants felt signicantly more immersed in the VR condition com-
pared to the CM condition, and to show if immersion played a mediating role in
any time compression efect we might nd.
.Procedure
We used a counterbalanced within-subjects design because we expected time per-
ception accuracy to be highly variable between people. There were two display
conditions (virtual reality [VR] and conventional monitor [CM]) as well as two
sets of mazes (A and B). Each participant played the game once in VR and once on
the CM, one of which used maze set A and the other used set B. Display condition
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and maze set were both counterbalanced to minimize order and maze diculty
efects.
Participants were asked to keep their phones and watches out of sight for the
duration of the experiment, and to sit in front of a computer at a desk in our
lab room. No clocks were visible to the participants, and research assistants in
adjacent rooms refrained from using time-related language. Figure  illustrates
the equipment used in each condition. A research assistant read instructions on
how to play the game, and the practice level was started while the controls were
described. Participants were told they could play the practice level for as long as
they wanted to get comfortable with the game, and that it was not timed. Once
they were ready to stop practicing, they could start the timed levels, which they
were instructed to end once they felt they had been playing for ve minutes. The
research assistant left the room and shut the door after the instructions to mini-
mize distractions and aural cues from outside the room.
We chose not to vary the duration of the intervals that participants were
instructed to produce because of our limited sample size. We set the target dura-
tion at ve minutes because it is a familiar and memorable unit of time, and we
expected it would be long enough to discourage deliberate counting of seconds,
but short enough to minimize fatigue efects (especially in the second sessions).
When the participant ended the timed levels, the elapsed time in seconds since
the end of the practice level was automatically recorded in a text le, along with
their practice time and the level that the participant had reached. No feedback
about how much time had actually passed was given to the participant. Then, the
research assistant briey reminded the participant of the instructions and started
the second game, which used the display condition and maze set that were not
used in the rst game.
Figure 2.Illustrations of the virtual reality and conventional monitor display conditions.
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After both versions of the game were completed, the participant was brought to
a new room to complete a post-task survey (see Materials above).
3. Results
We conducted a two-way mixed-efects ANOVA with factors of starting display
type (VR or CM) and block number (rst or second). The results, shown in Fig.,
revealed a main efect of block number (F, = ., p=., ηp2= .),
indicating that the mean duration of intervals produced in the second block
(.s) was signicantly longer than that of intervals produced in the rst block
(.s). Importantly, there was a main efect of starting display type (F,=.,
p=., ηp2=.). Participants who played the VR game rst (and the CM
game second) produced longer intervals than participants who played the CM
game rst (and the VR game second). This means that the efect of display type
on interval duration depends on order: in the rst block, participants in the VR
condition produced longer durations (.s on average) than participants in the
CM condition (.s), whereas in the second block, VR durations (.s) were
shorter than CM durations (.s). Furthermore, we found a strong correlation
between participants’ rst and second interval durations (r=., p<.,
Figure 3.A line graph showing mean produced interval durations (with standard error bars) organ-
ized by condition and starting display. Participants who started with virtual reality (VR) produced
longer intervals in both the rst and second blocks, and second block intervals were longer than
rst-block intervals. The dotted horizontal reference line shows the position of an accurate interval.
CM, conventional monitor.
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n=), suggesting individuals’ second intervals were heavily anchored to their
rst ones. Because of this order efect, we limit our remaining analyses to rst-
block responses.
As shown in Fig. , rst-block participants in the VR condition let signicantly
more time pass than rst-block participants in the CM condition before indicating
that ve minutes had passed (t=., p=., d=.). VR intervals were
.s long (SD=.) on average, and CM intervals were .s (SD=.)
on average. This means that in the VR condition, . more seconds (% CI, [.,
.]) passed on average before participants felt that ve minutes had elapsed.
This nding supports our rst hypothesis, that participants experience time com-
pression in VR compared to playing an identical game on a CM.
To rule out an account based on diferences in task diculty, we compared how
quickly participants in the two conditions completed the levels of the maze game.
Figure  shows that the relationship between interval duration and level reached
is described by a similar linear relationship in the two conditions. To determine
whether these slopes were signicantly diferent, we ran , bootstrap sam-
ples from each condition to compare the resulting best-t lines and found that
the % condence interval for the diference between best-t slopes in the VR
and the CM condition [−., .] contained zero.Therefore participants
across the VR and CM conditions completed levels at similar rates, suggesting
that the time compression efect cannot be attributed to participants spending
more time on each level in VR compared to CM and using the number of levels
completed as a proxy to decide when ve minutes had elapsed. Furthermore we
Figure 4.A bar graph showing mean interval durations produced in the virtual reality (VR) and
conventional monitor (CM) conditions (rst block only) with standard error bars. Participants in
the VR condition produced signicantly longer intervals. The horizontal reference line shows the
position of a true -min interval.
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found no signicant diference in practice time between conditions (t=−.
p>., d=.) suggesting it was not more dicult to learn the game in VR
than in CM.
We did not nd support for the hypothesis that produced interval durations
would be more variable in the VR condition. Although intervals produced in the
VR condition (SD=s) were slightly more variable than intervals produced in
the CM condition (SD=s), Levene’s test showed that there was no signicant
diference in interval variance between conditions (F,=., p>.).
The survey responses did not reveal a signicant relationship between interval
durations and previous experience with video games or with VR, nor was there a
signicant diference between conditions in rated diculty (either of the game
or of keeping track of time). This result conicts with our second prediction that
time estimation in VR would be more dicult, and that produced intervals would
therefore be more variable in VR compared to CM. However, because the survey
was administered after participants had completed both tasks, it is possible that
participants’ responses pertaining to one condition were confounded by their
experience with the other. In fact, we found no signicant diferences in ratings of
immersion between the VR and CM conditions. Only one of the  Likert scales
about immersion (“I did not feel like I was in the real world but the game world”)
appeared to be higher in VR compared to CM (t=., p=., d=.),
but this diference did not reach signicance at the Bonferroni-corrected alpha of
Figure 5.A scatterplot of each participant’s interval duration and the number of levels they reached
in the rst experiment block. The best-t lines have a xed y-intercept at  (a -s time interval would
correspond to level ), and the vertical reference line shows the position of an accurate interval.
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. (see Supplementary Table S for the complete immersion scale results).
The surprising lack of an immersion diference between conditions suggests that
administering the survey after both conditions were completed may have dimin-
ished our ability to detect an efect.
4. Discussion
These results constitute the rst evidence that VR as a medium produces a unique
time compression efect. At least one previous experiment (Schneider et al., )
successfully used VR to produce a similar efect, but the present study is the rst
to observe time compression as a signicant diference between VR and non-VR
experiences with otherwise identical content. Importantly, our results suggest
that there is something inherent about the VR interface (as opposed to a charac-
teristic of its content) that produces a time compression efect.
Most of the previously observed efects on prospective time estimation are
related to attention, but the signicance of our main nding does not appear to be
attributable to a diference in attentional demands. The tasks in both conditions
were of identical complexity and diculty; the two sets of maze levels were coun-
terbalanced across conditions, and participants in both conditions spent about
the same amount of time on each level.
The VR condition did present a simpler scene to the participant than the CM
condition (it had a narrower eld of view, and the physical lab environment was
not visible), but this is unlikely to explain our efect either. Visual-stimulus com-
plexity has been found to only afect retrospective estimates (Block & Zakay,
). If we were to repeat this experiment using retrospective estimates, we
would expect to nd shorter perceived intervals in the VR condition, because the
VR scene presents a smaller amount of information that could be later recalled
from memory. This would also be a kind of time compression efect, but assum-
ing that the participants’ attention remains on the screen during the interval, we
would expect a much weaker efect than the one we found. Based on Block and
Zakay’s () meta-analysis, though, stimulus complexity should have no signi-
cant efect on prospective estimation tasks like the one we used.
Arousal can also inuence prospective time estimation in general, but it is
highly unlikely to explain our main nding because of the direction of its efect.
Images displayed in VR have been found to elicit higher arousal than the same
images displayed on conventional monitors (Estupiñán et al., ), but higher
arousal is associated with time dilation, according to the attentional-gate model
(Zakay & Block, ). In the context of our study, this would predict that par-
ticipants in the VR condition would produce shorter intervals than participants
in the CM condition. Because produced intervals in the VR condition were in
fact longer, we conclude that arousal did not play a role in the main efect we
observed, either.
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One diference between our two conditions that does seem likely to be respon-
sible for the efect is that participants could not see their own body, or any repre-
sentation of it, in the VR condition. In pacemaker–accumulator models of time
perception, pulse generation is treated as an abstract module of the time esti-
mation process, but it is thought to be a function of bodily rhythms like heart
rate, breathing, or neural oscillations (Pollatos et al., ; Wittmann, ). The
model’s inclusion of arousal as an inuence on the pacemaker is based on this
assumption, and there is accumulating evidence that time estimation accuracy is
dependent on awareness of bodily rhythms. It has been found that time estimation
accuracy is signicantly correlated both with ability to estimate one’s own heart
rate (Meissner & Wittmann, ), and with heart rate variability itself (Cellini
et al, ). A more recent study found that people with high interoceptive
accuracy are less susceptible to emotion-induced distortions of time perception
(Özoğlu & Thomaschke, ).
Bodily awareness was measured as a participant variable in those studies, but
it can also be manipulated. An experiment which used a VR and non-VR version
of the same interactive environment found that bodily awareness was reduced
in VR (Murray & Gordon, ). Specically, the participants in the VR condi-
tion gave signicantly lower ratings on scales of cardiovascular, skin, and muscle
awareness. This is presumably related to the absence of any visible representation
of the users’ body in the VR scene.
The combination of these two ndings, () that prospective time estima-
tion accuracy is related to awareness of bodily rhythms and () that being in VR
reduces bodily awareness, suggests a likely explanation for the efect observed in
the current study: participants in the VR condition were less aware of the passage
of time because they were less aware of the bodily rhythms that form the basis of
prospective time perception.
This is notable because the most prominent models of prospective time esti-
mation do not account for interoceptive awareness as an independent inuence
on perceived interval durations. For example, pacemaker–accumulator models
like Zakay and Block’s () attentional gate include arousal, attention, and ref-
erence memory ‒ but not interoceptive awareness ‒ as inuences on prospective
time estimation. Because we suspect that a diference in interoceptive awareness
(and not in attention, arousal, or memory) best explains the VR-induced time
compression efect, models like these might be modied to account for intero-
ceptive awareness as an independent inuence on prospective time estimation.
Dedicated timing models (Ivry & Schlerf, ) such as the attentional-gate model
involve a pacemaker module that produces pulses that depend on bodily rhythms
such as heart rate, breathing, or neural oscillations. We propose that such models
might be amended to include interoceptive awareness as a factor that mediates
the reception of these pulses. Impairing interoceptive awareness would lead to
underestimations of time by reducing the number of pulses that ultimately reach
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the accumulator. Although prominent models so far have not treated interocep-
tive awareness as its own factor, our results suggest that it may afect time estima-
tion independently from attentional demands, arousal, and reference memory.
The durations of participants’ second intervals were heavily anchored to rst
interval durations. It could be that the time production task in the rst block
severely revised each participants’ reference for what a ve-minute interval feels
like, and caused them to use that new reference to produce the second interval.
Second intervals were also longer. This efect was exhibited by participants who
played the VR version rst and then switched to CM, as well as those who started
with CM and switched to VR. The greater durations of second block intervals could
be due to a novelty efect which may have dilated time perception more during
the rst block compared to the second block. Alternatively, participants may have
expected to complete more levels in a -min period during the second block after
having gained experience with the task. If participants expected to complete more
levels in the second block, and used the level reached in the rst block as a proxy
to indicate the passing of ve minutes, they may have purposely played additional
levels in the second block. In fact, participants did on average play one additional
level in the second block, but the rate of completing levels was no faster compared
to the rst block.
It is well established that order efects in general can confound results when
counterbalancing is not used, but in our case the order efect was so overwhelm-
ing that the time compression efect becomes completely obscured if we analyze
our data without regard for condition order. This suggests that counterbalancing
may not be sucient for experiments which use interval production tasks, and
that future studies should use between-subjects designs when possible.
A follow-up experiment could further investigate the role of interoception in
VR-induced time compression by having participants complete a bodily aware-
ness scale after they complete the maze game. Using a between-subjects design in
such an experiment would allow the questionnaire to be administered immedi-
ately after a single playthrough of the maze game, making it more valid than ours
(which was administered after participants had completed both conditions).
Including an additional VR condition with a virtual body representation could
also help clarify the role of body visibility in time perception (and more broadly,
in bodily awareness). It is unclear now if hiding one’s body from view is enough
to reduce bodily awareness, or if the efect depends on the VR-induced feeling
of presence that makes the user feel as though they are in a place that is remote
from their body. If adding a virtual body were found to both increase bodily aware-
ness and mitigate the time compression efect, that would support the idea that
reduced body visibility is responsible for the main efect we observed. If that
manipulation were found to have no impact on bodily awareness or the time com-
pression efect, it would suggest that the efect depends not on body visibility but
on some higher-level feeling of virtual presence.
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Another limitation of the present experiment is that we did not vary the dura-
tion of the interval that participants were asked to produce. Bisson and Grondin
() and Tobin et al. () found that during gaming and internet-surng
tasks, signicant time compression efects were only evident during longer ses-
sions (around min or longer). The authors of those studies note that this dif-
ference may be due to the time estimation methods they used: participants were
asked to verbally estimate durations, and might have rounded their answers to
multiples of ve minutes. This rounding bias would have a much stronger inu-
ence on the results of their shorter-interval trials (min) than on their longer-
interval trials (, , or min). Our nding of a time compression efect on
a ve-minute scale suggests that the interval production method we used likely
protected our results from such a rounding bias. It is unclear whether or how the
VR-induced efect we found might depend on the target duration of the produced
interval. Future studies investigating this efect could explore this inuence by
instructing participants in diferent conditions to produce intervals shorter and
longer than ve minutes.
If transient reminders like the one we used are employed during prospec-
tive time estimation tasks, we recommend that the durations of the interval be
pseudo-randomized. Our reliably periodic reminder may have helped our partici-
pants produce more accurate intervals in both conditions. Making the cue unreli-
able might reveal a larger efect, which could be crucial in experiments that test
time perception in more delicate contexts.
.Implications for VR Experience Design
An average of .% more real time passed for participants who played the VR
game than for those in the control group ‒ with no diference in perceived dura-
tion. If this efect proves to generalize to other contexts at similar magnitudes, it
will have signicant implications. Keeping track of time accurately is desirable in
most situations, and impairing that ability could be harmful.
Time compression might cause VR users to unintentionally spend excessive
amounts of time in games, especially as HMDs become more comfortable to
wear for long sessions. Even non-immersive games entail some risk of addic-
tion, which has been associated with depression and insomnia (Kuss & Griths,
). VR games may pose a greater risk of interfering with their players’ sleep
schedules, mood, and health by reducing their ability to notice the passage of
time. Developers should take care not to create virtual ‘casinos’; a clock should
always be easily accessible, and perhaps even appear automatically at regular
intervals.
On the other hand, time compression efects can be desirable in situations
that are unpleasant but necessary, and there are potential applications that could
take advantage of the efect in a benecial way. VR might be used, for example,
to reduce the perceived duration of long-distance travel. More importantly, the
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value of using VR to make chemotherapy more bearable (Schneider et al., )
is supported by the current study. Especially considering that VR has been used
successfully as an analgesic (Hofman et al., ), VR experiences could be simi-
larly applied to reduce the negative psychological impact of other painful medi-
cal treatments. Our interpretation of the results suggests that other equipment
or treatments which reduce bodily awareness, such as sensory deprivation tanks,
may also be useful for producing time compression efects.
Supplementary Material
Supplementary material is available online at:
https://doi.org/./m.gshare.
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