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R E S E A R C H A R T I C L E Open Access
Is virtual reality always an effective stressors for
exposure treatments? some insights from a
controlled trial
Federica Pallavicini
1*
, Pietro Cipresso
1
, Simona Raspelli
1
, Alessandra Grassi
2
, Silvia Serino
1
, Cinzia Vigna
1
,
Stefano Triberti
1
, Marco Villamira
3
, Andrea Gaggioli
1
and Giuseppe Riva
1,2
Abstract
Background: Several research studies investigating the effectiveness of the different treatments have demonstrated
that exposure-based therapies are more suitable and effective than others for the treatment of anxiety disorders.
Traditionally, exposure may be achieved in two manners: in vivo, with direct contact to the stimulus, or by imagery,
in the person’s imagination. However, despite its effectiveness, both types of exposure present some limitations
that supported the use of Virtual Reality (VR). But is VR always an effective stressor? Are the technological
breakdowns that may appear during such an experience a possible risk for its effectiveness?
Methods: To answer these questions we compared changes following the exposure to an academic examination,
one of the most universal examples of real-life stressors, in a sample of 39 undergraduate students. The same
experience was offered using text (TX), audio (AU), video (VD), and VR. However, in the virtual environment we
manipulated the experience introducing technological breakdowns. The Post Media Questionnaire (PMQ) and the
Slater-Usoh-Steed Presence Questionnaire (SUS) were administered to each participant in order to evaluated self-
report measures of anxiety and relaxation and the level of presence experience during media exposure.
Electrocardiogram (ECG), Thoracic Respiration Signal (RSP) and Facial corrugator supercilii muscle Electromyography
(EMG) were recorded in order to obtain objective measures of subjects’emotional state.
Results: Analyses conducted on PMQ showed a significant increase in anxiety scores and a mirror decrease in relax
scores after all our emotional procedures, showing that all the condition were effective in inducing a negative
emotional response. Psychometric scores and psychophysiological indexes showed that VR was less effective than
other procedures in eliciting stress responses. Moreover, we did not observe significative difference in SUS scores:
VR induced a sense of presence similar to that experienced during the exposition to other media.
Conclusions: Technological breakdowns significantly reduce the possibility of VR eliciting emotions related to
complex real-life stressors. Without a high sense of presence, the significant advantages offered by VR disappear
and its emotional induction abilities are even lower than the ones provided by much cheaper media.
Trial registration: ClinicalTrials.gov Identifier: NCT01683617
Keywords: Stress, Emotion elicitation, Virtual reality
* Correspondence: f.pallavicini@auxologico.it
1
Istituto Auxologico Italiano IRCCS, Applied Technology for Neuro-
Psychology Laboratory, Milan, Italy
Full list of author information is available at the end of the article
© 2013 Pallavicini et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Pallavicini et al. BMC Psychiatry 2013, 13:52
http://www.biomedcentral.com/1471-244X/13/52
Background
Different research studies have shown that exposure-
based therapies are more suitable and effective than others
in the treatment of anxiety disorders [1-9].
Exposure is a process in which the patient is progres-
sively exposed to the feared stimulus or the situation that
provokes anxiety. Traditionally, exposure is experienced
in two ways: by imagery in the person’s imagination, or
in vivo, with direct contact to the stimulus.
Nevertheless, all roses have thorns, and this is true for
both types of exposure, too. On one side, some patients re-
port difficulties when asked to imagine the feared situation;
furthermore, emotions have been shown to modulate
visual imagery and perception [10], impairing visualization
of detailed scenes. On the other side in vivo exposure
is not fully under the control of the therapist and
requires a high effort in terms of money and time
expenditure.
To overcome these issues an emerging approach is the
use of Virtual Reality Exposure Treatments (VRET) [11-15].
Compared to traditional methods, VR has the advantage
to elicit a sense of presence in users, defined as the “feeling
of being in a world that exists outside of the self”[16,17].
Another advantage of VR is that in such a setting, as in
the real world, the subject can manipulate and interact
with the environment differently from all the other techni-
ques in which users are passive and not active [13,18]. It is
also possible to grade the intensity of the stimulus follow-
ing the personal needs of each patient. In this way, the
patient feels less uncomfortable about the treatment and
his/her motivation increases [19]. Recently different quan-
titative meta-analyses, have been conducted on studies
reporting VRET treatments. Parson and Rizzo [20] ana-
lyzed data from 21 studies who have evaluated anxiety
and/or phobia before and after VRET. They conclude
that VRET has a statistically large effect on all affective
domains, and thus it is a relevant approach to reduce
anxiety-related symptoms. They conclude that VRET has a
statistically large effect on all affective domains, and thus it
is a relevant approach to reduce anxiety-related symptoms.
Similarly, Powers and Emmelkamp [21] provide effect size
estimates for virtual reality treatment in comparison to
in vivo exposure and other control conditions. They
found a predictable larger effect of VRET compared to
the control conditions; but more interestingly, VRET
outperformed in vivo exposure.
But is VR always an effective stressor? Are the techno-
logical breakdowns that may appear during such an ex-
perience a possible risk for its effectiveness?
Unfortunately only a few studies compared the efficacy
of VR in inducing an emotional response with other
media and/or with real-life reactions [22-24]. These
studies also have the limitation to investigate very
simple emotive reactions, not so complicated as might
be a response related to a real-life stressor. Recently,
Hartanto and colleagues investigated the effects of three
different interruption mechanisms on subjective experi-
ence during a VRET session for social phobia with
scripted avatar-patient dialogues [25]. Specifically, the
study examined three interruption mechanisms: (1) dia-
logue dependent, that occurs freely in the flow of the
dialogue; (2) speech dependent, that occurs during the
pauses in the dialogue; and (3) context independent,
that is randomly. Although, the dialogue dependent
interruption seems superiors on the perceived dialogue
flow, on the user preference and on the dialogue replies,
participants rated presence highest for the context inde-
pendent mechanism. According to Riva and Mantovani
[26] indeed, we are present in an environment - real
and/or virtual - when we are able, inside it, to intuitively
transform our intentions in actions.
Based on the current status of presence research, much
uncertainty remains about its usefulness for emotional
responses induction and VRET. Only weak evidence for a
relationship between presence and emotional responses
has been found [22,27], and no study has yet addressed
this relationship. In other words, it is still unclear whether
VR with low measured presence is characterized by a
reduced effectiveness in inducing negative emotional
responses compared to other traditional procedures.
According to these theoretical premises, we manipu-
lated the level of presence by creating a virtual environ-
ment with two technical breakdowns: the head tracking
was randomly reversed for 20 seconds during the experi-
ence and the avatars’lips didn't move at the same time
as their voice. We argued that these two kinds of tech-
nical breakdowns reduce the capability of VR in support-
ing the intentions of the user and its capability to elicit
emotive reactions.
Hence, we compared changes following the exposure to
an academic examination, one of the most universal exam-
ples of real-life stressors, in a sample of 39 undergraduate
students. The same experience was offered using text,
audio, video, and “impoverished”VR.
Methods
Aim of the study
The general goal of this study was to compare the effi-
cacy of different media in eliciting negative emotional
responses. In particular, we wanted to examine if techno-
logical breakdowns that appeared during VR could reduce
its effectiveness in comparison with other media (text,
audio, and video) in arousing emotions related to a real-
life stressor.
To compare the efficacy of these techniques, we
compared the relative effectiveness of different pres-
entation modalities of the same stressor (an oral aca-
demic examination).
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In particular the following hypotheses were tested:
a. The four experimental situational emotional
induction procedures are effective in eliciting a
negative emotional response in undergraduate
students.
b. The four experimental situational emotional
induction procedures elicit different intensities of
emotional response.
c. The VR experience, when associated to technology
breakdowns, is less effective than other media in
eliciting the negative emotional response.
d. “Impoverished”VR induces a sense of presence
similar to those experienced during the exposure to
other media.
Participants
The experimental sample included 41 students. The mean
age of the sample was 21.15 ± 3.6, with a mean years of
school education of 13.59 ± .498.
Students were recruited from the University of IULM,
Italy. In order to be included in the study, students had
to meet the following criteria: (1) absence of heart, blood
pressure, or major medical diseases; (2) Age between 20
and 30 years; (3) Absence of pharmacotherapy or other
medications that might interfere with the measures being
assessed (e.g, psychoactive medications; antihypertensives);
(4) Absence of psychiatric disorders; (5) Absence of neuro-
logical diseases, mental retardation, psychosis, alcohol or
drug dependence; (6) No migraine, headache, or ves-
tibular abnormalities. Subject eligibility was determined
via subject-reported medical history.
Of these, two did not fulfill the inclusion criteria and
were excluded. Therefore, 39 students were included in
the statistical analysis of psychometric questionnaires,
while only 34 were included in the physiological one.
Before participating in the study, each participant was
provided with written information about the study and
was invited to give written consent for the inclusion.
Participants were also asked to not smoke or assume
caffeine during the day of the experiment. The study
received ethical approval by the Ethical Committee of
the Istituto Auxologico Italiano.
Negative emotions elicitation
According to an emotional narrative validated in a prelim-
inary study [28], we created an audio, a text, a video and a
virtual environment based on that script. The emotional
imagery narrative was based on methods developed by
Lang and his colleagues [29] and further adapted by Sinha
and colleagues [30,31]. In the emotional imagery script,
alluding to an oral academic examination, specific details of
the situation were elicited referring to specific stimulus and
response particulars, including physical and interpersonal
context details, verbal and cognitive attributions regarding
the people involved. A sample of the script used in this
study follows above:
“It’s your last exam before graduating. The next exam
session will be only the next year. You know that, if
you fail, you will have to wait some months to
graduate. You feel very nervous. In the exam’s room
you see four of your classmates. They are talking
about the examination and they seem to be very
worried and troubled. They tell you that all of them
failed the exam and that the professor is very strict.
Your anxiety increases. You feel your breath
becoming heavy. Your heart is faster and faster (...)”.
Laboratory assessment
Psychometric assessment
The following psychometric questionnaires were admi-
nistered to each participant at the start of the experi-
ment and after each experimental condition:
Post Media Questionnaire (PMQ, [32,33]).The Post
Media Questionnaire (PMQ) was used to assess the
emotions elicited by media exposure. In the
questionnaire participants rate the greatest emotions
experienced during the media experience (anxiety,
disgust, anger, fury, surprise, relax, happiness,
sadness) on a 7-point likert scale
Slater-Usoh-Steed Presence Questionnaire (SUS,
[34]): The Presence Questionnaire was used to
assess the level of presence experience during media
exposures. In the questionnaire participants rate the
characteristics of the media experience (feeling of
being there, realism, involvement) and on a 7-point
likert scale.
Psychophysiological assessment
At the beginning, during and at the end of the laboratory
session, electrocardiogram (ECG), Thoracic Respiration
Signal (RSP) and Facial corrugator supercilii muscle Elec-
tromyography (EMG) were recorded in order to obtain
objective measures of subjects’emotional state.
Collected data were analyzed using Matlab 7.0 (The
Mathworks, Natick, MA). Cardiovascular and respiratory
activities were monitored to evaluate both voluntary and
autonomic effect of respiration on heart rate, analyzing
both inter-beat (R-R) interval extracted from electrocar-
diogram and respiration (from a chest strip sensor). The
respiration signal was filtered to produce a smooth sinus-
oidal signal. The Respiration Rate (RSP_Rate) index repre-
sents the peak-to-peak time (max-to-max distance of
the sinusoid). Furthermore, following the guidelines of
Task force of the European Society of Cardiology and the
North American Society of Pacing and Electrophysiology,
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a typical Heart Rate Variability (HRV) spectral method
indexeswereusedtoevaluatetheautonomicnervous
system response [35-40]. At this purpose spectral ana-
lysis was performed using Fourier spectral methods with
custom software. The rhythms have been classified as
very low frequency (VLF, <0.04 Hz), low frequency (LF,
from 0.04 to 0.15 Hz), and high frequency (HF, from
0.15 to 0.5 Hz) oscillations. This procedure enabled us
to calculate the HF index [39,40].
The raw electromyography is a collection of positive and
negative electrical signals; their frequency and amplitude
give us information on the contraction or rest state of
themuscle.AmplitudeismeasuredinμV(micro-Volts).
As the subject contracts the muscle, the number and
amplitude of the lines increases; as the muscle relaxes, it
decreases. We considered the EMG Root Mean Square
(EMG_RMS) for rectifying the raw signal and converting
it to an amplitude envelope. In this study, we were not
interested in frequency related to muscle fatigue.
To summarize psychophysiological measures used in
this study:
HF: High Frequency, 0.15 to 0.5 Hz oscillations in
R-R interval extracted from Electrocardiogram. In
stressful situations this index tends to decrease from
baseline.
EMG_RMS: Root Mean Square EMG from facial
corrugator supercilii muscle Electromyography. In
stressful situations this index tends to increase from
baseline
RSP_Rate: peak-to-peak time from Respiration
signal. In stressful situations this index tends to
increase from baseline
Psychophysiological data were obtained using the
NeXus-4 equipment, with the BioTrace+ software for
recording signals, developed by Mind Media. The module
gets analog data coming from different physiological sen-
sors and, after conditioning and digitalizing, sends them to
a host Personal Computer (PC) using a wireless connection.
Experimental protocol
A within-subjects design was used to compare self-reported
anxiety and relax measures from a pre-condition baseline
to each of the four experimental conditions. Participants
acted as their own controls.
Specifically, the study compared the following conditions:
Condition 1: Virtual Reality (VR). In the VR
condition participants were asked to wear a head-
mounted display (Vuzix VR Bundle with twin high-
Figure 1 Screenshot from VR condition. Figure illustrates virtual
environment representing an academic oral examination in
a classroom.
Figure 2 Time scheduled of the experiment.
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resolution 640x480 LCD displays, 920,000 pixels,
iWear
W
3D compliant) in order to have a 3D view of
the virtual scene. The virtual environment was
rendered using a portable computer (ACER ASPIRE
with CPU Intel
W
Core
™
i5 and graphic processor
Nvidia GeForce GT 540M). Participants also had a
joystick (Xbox Controller), which allowed them to
explore and to interact with the environment. The
virtual scene represented an academic oral examination
in a classroom (the virtual environment is included
in NeuroVR 2.0 [23], a free open source software
that was previously used in different emotion inducing
experiments [22,24]. In all of them the scenes of the
environment were able to elicit a strong emotional
response and feeling of presence that was similar [22]
or even higher [24] than the real scene. Based on
these previous studies, we assumed that the virtual
scene without technical breakdowns would be very
effective in eliciting negative emotional response.
In the selected scene the individual was asked to
enter in the class and meet a group of students
who commented on the difficulty of the exam and
how the professor was very tough. Then, he/she
had to approach the professor who was just
rejecting a student. Finally his/her name was called
by the professor and asked to start the exam.
During the experience the participant also experienced
two technological breakdowns: the head tracking was
randomly reversed for 20 sec during the experience
and the students’lips didn't move at the same time
as their voice. The complete experience was about
3minuteslong.
Condition 2: Audio (AU). Subjects were asked to
imagine themselves as vivid as possible during an
academic oral examination, following an audio
narrative matching the VR experience. Script
development procedures was based on methods
developed by Lang and his colleagues [29], and
further adapted and validated in our previous study
[28]. During the imagery exposure subjects were
asked to close their eyes and to imagine the situation
described. The audio narrative was about 3 minutes
long and was played through the computer speakers.
(Compliant Standards High Definition Audio)
Condition 3: Texts (TX). Based on the script used in
the Imagery Exposure, a script in a written form was
developed. Participants were asked to read a text in
which an academic oral examination is described.
The script was defined with sufficient details to
induce subjects to enter in the story, as
hypothesized by Geerig [41]. The text was read in
about 3 minutes on the 17”computer screen.
Condition 4: Video (VD). In the VD condition
participants were exposed to a video, based on the
Imagery Exposure script, and using the same actors
involved in the VR scene, showing the same situation
described before. The video was about 3 minutes long,
too. Participants watched the video on the 17"
(1920x1200) computer screen (Figure 1).
Participants were randomly assigned to the order in
which conditions were presented. The order of presenta-
tion of each experimental condition was counterbalanced
for each participant following an established randomization
schema obtained from http://www.randomizer.org/.
Before starting the experiment each participant was
provided with written information about the study and
was invited to give written consent for the inclusion. Then,
each participant was submitted to a subject-reported med-
ical history interview.
At the start of the experimental session, participants
were seated at a desk in front of a computer monitor. The
eye-to-display distance was about 0.75 meters. Participants
were connected with biosensors for recording their psy-
chophysiological parameters (heart rate, respiration, and
facial corrugator supercilii muscle activity). A baseline
measure of these signals was registered for 3 minutes in
rest condition, with eyes opened. Once the physiological
baseline was recorded, the experimental session started
and psychophysiological signals were recorded until the
end of all the tasks. Then, in order to measure the psycho-
logical variations occurring during the different exposure
conditions, subjects completed an adapted version of the
PMQ in order to assess their perceived level of anxiety
Table 2 Mean and Standard deviation of relax scores
assessed trough the PMQ Questionnaire before and after
all the four conditions
Time
Condition Pre Post
Virtual Reality 4.16 (1.14) 2.84 (1.6)
Video 4.14 (1.25) 3 (1.87)
Audio 4.24 (1.34) 2.43 (1.53)
Text 4.14 (1.22) 3.03 (1.6)
Table 1 Mean and Standard deviation of anxiety scores
assessed trough the PMQ Questionnaire before and after
all the four conditions
Time
Condition Pre Post
Virtual Reality 2.65 (1.16) 3.78 (1.88)
Video 2.41 (1.18) 4.27 (1.83)
Audio 2.51 (1.3) 4.76 (1.94)
Text 2.49 (1.23) 4.35 (1.94)
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and relax immediately before and after each condition.
After each exposure condition they completed also the
SUS to assess presence’s level experienced. Before each
condition there was a 3 min baseline during which par-
ticipants were asked to stay completely relaxed with
open eyes, while their physiological parameters were
recorded (Figure 2).
Results
Data were entered into Microsoft Excel and analyzed using
SPSS and STATA. Change in psychometric and physio-
logical measures within subjects were calculated using
repeated measure ANOVAs.
Psychometric variables
To confirm that the stress induction was successful and
that participants were stressed and experienced a nega-
tive emotional state after the exposure to each condition
(VR, AU, VD, TX), we evaluated self-report measures of
anxiety and relaxation assessed through PMQ before and
after each condition. A 2 (time) × 4 (condition) repeated
measures ANOVAs on the mean scores were conducted
in order to compare the effect of time on anxiety and relax
scores depending on the specific condition.
Regarding anxiety, results showed a significant main ef-
fect of time, F (1,36) = 44.2, p < .001, ηp2 = .522. In particu-
lar, the mean score showed before (M = 2.51, SD = .168)
was lower than that assessed after (M = 4.29, SD = .275)
theexposuretoconditions.Themaineffectofcondition
was non-significant, F (3,108) = 2.56, p = ns, ηp2 = .066.
However, the interaction effect between time x condition
was significant, F (3,108) = 4.93, p < .05, ηp2 = .121, sug-
gesting that anxiety mean scores changed over time de-
pending on condition (Table 1).
A mirror result was obtained regarding relax level.
Results showed a significant main effect of time, F (1,36) =
41.1, p < .001, ηp2 = .533. In particular, the mean scores
showed before (M = 4.16, SD = .162) was higher than that
assessed after (M = 2.82, SD =. 233) the exposure to
conditions. The main effect of condition was non-
significant, F (3,108) = .887, p = ns, ηp2 = .024. However,
the interaction effect between time x condition was signifi-
cant, F (3,108) = 2.75, p < .01, ηp2 = .07, indicating that
relax mean scores changed over time depending on condi-
tion (Table 2).
To test for simple effects, we calculated the mean dif-
ference of self-report anxiety measures (score at the
baseline minus score after condition) for each condition.
A repeated measure ANOVA with condition as the
within factor revealed a significant main effect of condi-
tion in anxiety scores, F (3,114) = 4.59, p < .005, and in
relax scores, F (3,114) = 2.82, p < .05 (Table 3).
In particular, repeated-measures t-tests (using a Bonferroni
adjustment α= .05/3 = .017) showed that the mean differ-
ence in anxiety scores was significantly lower in the VR
condition (M = −1.02, SD = .325) than in the AU condition
(M = −2.28, SD = .322), t(36) = −1.256, p < .01, ES = .385;
Then, in order to evaluate self-report measures of pres-
ence, we analyzed the SUS total score (sum of item 1, 2
and 3) assessed after each condition. A one-way ANOVA
on the mean scores was conducted in order to test
whether SUS scores changed depending on the specific
condition.
Analyses showed no significant main effect of condition,
F(3,111)=.084,p=ns(Table4).
Psychophysiological variables
A repeated measures analysis of variances was also con-
ducted in order to test whether psychophysiological indexes
changed depending on the specific experimental procedures.
Due to complexity of signal processing some subjects
turned in a problematic bio signal, composed by many
artifacts and/or missing values. Thus, some subjects have
been excluded from analysis, in particular we excluded
nine subjects form HF computation and eight subjects
from EMG_RMS and RSP_Rate computation. So, even-
tually, the psychophysiological statistical analyses have
been performed on 32 or 33 subjects, a number well-
Table 4 SUS total score after each condition
Condition Virtual Reality Audio Video Text Fp
Presence 12.1 (4.03) 12.4 (4.15) 12.3 (4.35) 12.1 (3.75) .084 .969
ANOVA did not reveal a significative main effect of condition.
Table 3 Mean and Standard Deviation of main difference in anxiety and relax scores (score at the baseline minus score
after condition)
Condition
Virtual Reality Audio Video Text Fη
p
2
p
Anxiety −1.02 (.325) −2.28 (.322) −1.64 (.37) −1.82 (.32) 4.59 .525 .000***
Relax 1.07 (2.03) 1.89 (1.41) 1.12 (1.52) 1.28 (1.94) 2.82 .069 .042*
***p < 0.001, **p < 0.01, *p < 0.05.
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recognized to be of good level in these kinds of studies.
More, a statistical power analysis confirmed the fairness
of our sample size (Table 5).
Results showed a main effect of condition for HF,
F(96,3) = 3.16, p < .028, EMG_RMS, F(99,3) = 16.1,
p < .001, and RSP_Rate, F(99,3) = 17.1, p < .001. In
particular, adjustment for multiple comparisons, with
Bonferroni correction, showed the significant differences
reported in Table 4 (Figure 3).
Discussion
Virtual Reality Exposure Treatment (VRET) is an emer-
ging approach for the treatment of anxiety disorders that
offers different advantages over classical imaginative and
in vivo exposure. Recently, different quantitative meta-
analyses have been conducted on studies reporting VRET
treatments supporting their efficacy in reducing anxiety-
related symptoms [11,12].
But is VR always an effective stressor? Are the techno-
logical breakdowns that may appear during such an experi-
ence a possible risk for its effectiveness? Different studies
suggested a possible link between emotional response and
the level of presence experienced in a virtual environment.
For example, Michaud and colleagues [42] experimentally
manipulated presence in a sample of heights phobics who
had to take an elevator and perform tasks on a scaffold out-
side of a 15-story building. When the immersion in the vir-
tual environment was conducted in a high-presence setting,
the level of anxiety was significantly higher than when the
immersion was conducted in a low-presence setting.
Table 5 Differences in main effects for HF, EMG_RMS and RSP_Rate
Measure (I) Condition (J) Condition Mean difference (I-J) Std. error p
HF Virtual Reality Audio 5.554 1.916 .041*
Video 5.477 1.719 .020*
Text 3.745 2.338 .714
EMG_RMS Virtual Reality Audio −5.489 1.092 .001***
Video −3.61 1.133 .020*
Text −4.898 1.032 .001***
RSP_Rate Virtual Reality Audio −3.626 .604 .001***
Video −2.22 .460 .001***
Text −2.808 .585 .001***
This table reports the comparison between Virtual Reality and the other stimuli (Audio, Video, Text), showing statistical significant differences for all the three
measures. ***p < 0.001, **p < 0.01, *p < 0.05.
Figure 3 A comparison within conditions with significance level showed accordingly. HF, EMG_RMS and RSP. Rate graphics per each
condition, showing deviation from baseline. The arrow (Stress zone) indicates the sense of the variation to indicate an increasing in stress in that
direction. It is clear from Figure 3 that Virtual Reality condition differs from other conditions in the direction quality, confirming that technological
breakdowns significantly reduce the possibility of Virtual Reality of eliciting emotions related to complex real-life stressors, besides the stressful
script used.
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Riva and colleagues [43] explored, too, the relationship
between presence and emotions experienced in VR. Their
data showed a circular interaction between presence and
emotions: on one side, the feeling of presence was greater
in the "emotional" environments; on the other side, the
emotional state was influenced by the level of presence.
Taken together these results underline the existence of
a bi-directional relationship between presence and emo-
tions. However, no previous studies investigated if the
reduction of presence induced by technological break-
downs may be accompanied by a reduced results efficacy
of VR as a stressor for exposure treatments.
To answer this question we compared changes following
the exposure to an academic examination in a sample of
39undergraduatestudents.Thesameexperiencewas
offeredusingtext,audio,video,andVR.However,inthe
virtual environment we manipulated the experience intro-
ducing two technological breakdowns: the head tracking
was randomly reversed for 20 seconds during the experi-
ence and the avatars’lips didn't move at the same time.
In the study we first investigated if our emotional induc-
tion procedures were really effective in eliciting an emo-
tional stress-related response. Results, in accordance with
our hypothesis, showed that conditions were effective in
inducing a stress-related response. We found a significant
increase in anxiety scores measured through PMQ and a
mirror decrease in relax scores after all our emotional
procedures.
In addition, we assumed that the four emotive induction
procedures elicits different intensity of responses and, in
particular, we hypothesized that VR, when experienced
with breakdowns, was less effective than traditional proce-
dures. As hypothesized, results showed significative differ-
ences in the psychometric scores and psychophysiological
correlates between the four experimental conditions. In
particular, results on anxiety scores assessed through the
PMQ showed that negative emotional response elicited
through VR was less effective than AU procedure. Psycho-
physiological indexes confirmed this interesting result and,
moreover, showed that VR was less effective in inducing a
stress-related response compared to the other conditions.
Results, in fact, showed an increased level from baseline in
EMG_RMS index, a well-known index of emotional
valence, in AU, VD and TX conditions, clearly indicate a
higher negative emotion for the participants. On the other
hand, VR condition showed no increased level from base-
line. Also RSP_Rate showed similar results, indicating
an accelerated respiration pattern in AU, VD and TX
condition and a decelerated one in the VR condition. This
confirms that Virtual Reality containing technological
breakdowns has not been able to induce stress, besides
the negative script. Finally, a further confirmation arises
from HF, an important index of Heart Rate Variability.
Decreases in HF is a well-recognized index of stress, more
it has been recognized as an index that works well with
different kind of stress, from a more cognitive working
load to a situational stress due to psychological individual
perception of environmental demands that exceed one's
own adaptive ability to meet them [44]. In our study,
lower level of HF for Audio, Video, and Text indicate a
stress measured by the means of this cardiovascular index.
Virtual Reality, on the opposite, showed an increased level.
Thus also for this index we can confirm that technological
breakdowns in Virtual Reality worked well.
Finally, results confirmed our fourth hypothesis. As we
expected, “impoverished”VR induced a sense of presence
similar to that experienced during the exposition to other
media. This data confirms the hypothesis that techno-
logical breakdowns impacted the VR efficacy in inducing a
sense of presence in the user, creating break in presence
[26,44]. Moreover, this fact was associated in our study
with less effectiveness of VR in eliciting a negative emo-
tional response compared to other media.
Conclusions
In conclusion, even if using VR it is possible to experience
more presence than in real life [24,45], or to generate a
body transfer illusion [46], it is also possible to experience
less presence than reading a text or watching a video.
Therefore, if the focus is on designing applications capable
of eliciting emotions with the goal of reducing or modify-
ing them (as in psychological therapy), the environments
must be able to induce a high feeling of presence. For this
reason an important goal of VR developer is to guarantee
that the virtual experience offered to their user is smooth
and transparent enough to provide a high level of presence
through a full support to the intentions of the user. With-
out it, the significant advantages offered by VR disappear
and its emotional induction abilities are even lower than
the ones provided by much cheaper media.
Abbreviations
AU: Audio; ECG: Electrocardiogram; EMG: Electromyography;
EMG_RMS: Electromyography Root Mean Square; HF: High Frequency;
HRV: Heart Rate Variability; LF: Low Frequency; μV: Micro-Volts; PC: Personal
Computer; PMQ: Post Media Questionnaire; R-R: Inter-beat; RSP: Thoracic
Respiration Signal; RSP_Rate: Respiration Rate; SUS: Slater-Usoh-Steed
Presence Questionnaire; TX: Texts; VD: Video; VLF: Very Low Frequency;
VR: Virtual Reality; VRET: Virtual Reality Exposure Treatments.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
FP prepared the first draft of the manuscript. SR, AG and FP supervised the
study in its clinical aspect. FP, GR, SS and ST collected literature material and
supervised the background of the study. PC supervised the
psychophysiological aspect of the study. CV created the study technological
materials. GR, PC and SS developed the first draft manuscript into the final
version suitable for publication. MV, AG and GR conceived the idea of the
study and supervised its scientific design. All authors read and approved the
final manuscript.
Pallavicini et al. BMC Psychiatry 2013, 13:52 Page 8 of 10
http://www.biomedcentral.com/1471-244X/13/52
Acknowledgements
The present work was supported by the European funded project
"Interstress”–Interreality in the management and treatment of stress-related
disorders (FP7- 247685).
Author details
1
Istituto Auxologico Italiano IRCCS, Applied Technology for Neuro-
Psychology Laboratory, Milan, Italy.
2
Department of Psychology, Catholic
University of Milan, Milan, Italy.
3
Iulm University, Milan, Italy.
Received: 18 July 2012 Accepted: 7 February 2013
Published: 11 February 2013
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Cite this article as: Pallavicini et al.:Is virtual reality always an effective
stressors for exposure treatments? some insights from a controlled trial.
BMC Psychiatry 2013 13:52.
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