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The Trier Social Stress Test (TSST) is a reliable social-evaluative stressor. To overcome limitations of the in vivo TSST, a standardized virtual reality TSST (VR-TSST) was developed. The present study compares the emotional (anxiety) and physiological (heart period and variability) response to a VR-TSST with an in vivo TSST and a control condition. Participants took part in either an in vivo TSST (N = 106, 64% female), VR-TSST (N = 52, 100% female), or a control TSST (N = 20, 40% female). Mixed linear modeling examined response profile differences related to TSST type. While there was an equivalent anxiety response to the in vivo TSST as the VR-TSST, we found a smaller heart period and heart rate variability response in VR-TSST compared to the in vivo TSST, especially in response to the math part of the test. The present findings demonstrate that social evaluative stress can be successfully induced in a VR setting, producing similar emotional and slightly attenuated cardiovascular responses.
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International Journal of Psychophysiology 161 (2021) 27–34
Available online 14 January 2021
0167-8760/© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (
Multi-modal responses to the Virtual Reality Trier Social Stress Test: A
comparison with standard interpersonal and control conditions
M.A. Fallon
, M.M.E. Riem
, L.E. Kunst
, W.J. Kop
, N. Kupper
Business School, University of Mannheim, Mannheim, Germany
Center of Research on Psychological & Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
Behavioral Science Institute, Radboud University, the Netherlands
Clinical Child & Family Studies, Faculty of Behavioral and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
Trier Social Stress Test
Virtual reality
Psychosocial stress
Cardiovascular responses
Heart rate variability
The Trier Social Stress Test (TSST) is a reliable social-evaluative stressor. To overcome limitations of the in vivo
TSST, a standardized virtual reality TSST (VR-TSST) was developed. The present study compares the emotional
(anxiety) and physiological (heart period and variability) response to a VR-TSST with an in vivo TSST and a
control condition. Participants took part in either an in vivo TSST (N =106, 64% female), VR-TSST (N =52,
100% female), or a control TSST (N =20, 40% female). Mixed linear modeling examined response prole dif-
ferences related to TSST type. While there was an equivalent anxiety response to the in vivo TSST as the VR-TSST,
we found a smaller heart period and heart rate variability response in VR-TSST compared to the in vivo TSST,
especially in response to the math part of the test. The present ndings demonstrate that social evaluative stress
can be successfully induced in a VR setting, producing similar emotional and slightly attenuated cardiovascular
1. Introduction
The association between psychological distress and disease, partic-
ularly cardiovascular disease, is well-established in research (Cohen
et al., 2007). The mechanisms underlying this association have been
studied in laboratory experiments, illustrating that acute lab stressors
provoke disease-relevant physiological responses. One of the most reli-
able and widely used laboratory tests for studying the physiological
stress response is the Trier Social Stress Test (TSST) (Dickerson and
Kemeny, 2004). The TSST is administered in an experimental setting,
which involves a socially-evaluated public speaking and a mental
arithmetic task, and is conducted face-to-face with trained evaluators.
Cognitive effort, the setting, and the social evaluation aspect all
contribute to the observed physiological stress response (Kirschbaum
et al., 1993). The TSST reliably induces neuroendocrine, cardiovascular,
and immune responses (Allen et al., 2014). The observed physiological
response evoked by the TSST makes it a valuable tool for studying
biological mechanisms relevant to the association between psychosocial
factors and adverse disease progression.
Conducting the TSST in a laboratory setting (in vivo) has several
limitations that can interfere with the use of this procedure in a broad
range of clinically relevant settings. First, variations in the administra-
tion of the TSST show differential impacts on physiological responses.
Variations in the attentiveness of the evaluators and the extent to which
they are critical of the participant can affect the observed physiological
responses (Goodman et al., 2017). Limiting and controlling for varia-
tions in facial expressions and body gestures of evaluators can, however,
be difcult in a face-to-face experimental setting and across different
laboratories. Second, the stationary nature of the TSST may be limiting
its capability to measure stress responses outside a laboratory setting.
For example, participants and evaluators need to be in the same loca-
tion, which means it cannot easily be administered in a wide variety of
research environments (e.g. functional magnetic resonance imaging
scanner or eld applications).
To overcome the limitations of the in vivo TSST, researchers have
utilized a virtual reality TSST (VR-TSST). There has been limited
research, however, comparing the emotional and physiological re-
sponses to a VR-TSST with an in vivo TSST. Illustrating that a VR-TSST
can produce reliable emotional and physiological responses compara-
ble to an in vivo TSST would lend credibility to the utilization of a VR-
* Corresponding author at: Center of Research on Psychological & Somatic Disorders, Department of Medical and Clinical Psychology, Tilburg University, the
E-mail address: (N. Kupper).
Contents lists available at ScienceDirect
International Journal of Psychophysiology
journal homepage:
Received 2 July 2020; Received in revised form 12 January 2021; Accepted 12 January 2021
International Journal of Psychophysiology 161 (2021) 27–34
TSST in a broad array of clinical and research settings. Such ndings
could also help researchers to better understand the mechanisms linking
psychosocial stressors to disease by studying these processes outside of a
laboratory setting. Moreover, the VR-TSST could eliminate variations in
attentiveness and criticalness of evaluatorsthrough a more controlled
research environment.
It may not be immediately apparent why a VR-TSST would produce a
physiological response comparable to an in vivo TSST. Because partici-
pants are, in a way, observing the psychosocial stressor via the VR de-
vice, rather than directly experiencing it face-to-face, they might feel
less threatened by it. However, research suggests that social engagement
in virtual reality can indeed be realistic and comparable to real-life in-
teractions (Grinberg et al., 2014; Guadagno et al., 2007; Knowles et al.,
2017). Moreover, realistic social interactions in virtual reality increase
feelings of immersion, which is associated with usersmotivation and
engagement of the virtual reality space (Schultze, 2010). Thus, the social
interactions in a VR-TSST could sufce to activate representations of
reality and sufciently produce a physiological stress response compa-
rable to an in vivo TSST.
Prior research has attempted to validate versions of a VR-TSST
(Fallon et al., 2016; Jonsson et al., 2010; Kotlyar et al., 2008;
Montero-Lopez et al., 2016; Ruiz et al., 2010). However, only few
studies directly compare cardiovascular responses of an in vivo TSST to
VR-TSST. Studies that have made a direct comparison report similar to
somewhat smaller increases in heart rate (Shiban et al., 2016; Zimmer
et al., 2019) and heart rate variability in response to a speech task
(Kothgassner et al., 2016). However, the virtual reality condition in
these studies used head-mounted technology, which can cause partici-
pants to experience nausea and simulation sickness (Pan and Hamilton,
2018), conating the stress of vertigo with the psychosocial stress
evoked by the TSST. Moreover, head-mounted virtual reality systems are
expensive and are not feasible to use in unique research environments,
such as magnetic resonance imaging (MRI) scanners or in eld appli-
cations (Wilson and Soranzo, 2015). In the present study, we therefore
investigate the effects of a VR-TSST that requires no confederates, using
the Second Life platform, in comparison with an in vivo TSST and a
control TSST on cardiovascular activity (heart period and heart rate
variability) and negative emotion.
The current study uses an inexpensive and widely available online
virtual world technology presented on a computer screen as opposed to a
head-mounted display. To our knowledge, this study is the rst to
compare stress induced by a virtual TSST without head-mounted tech-
nology with stress levels induced by an in vivo TSST. If it were possible to
produce similar cardiovascular responses to a real-world TSST, it would
have several practical and experimental advantages (e.g. lower costs,
more standardization, and ability to evaluate stress responses outside a
laboratory). We hypothesize that the VR-TSST, using the Second Life
platform on a computer screen, will evoke changes in emotional and
cardiovascular reactivity similar to an in vivo TSST (H1). Moreover, we
expect that responses from the in vivo TSST will be signicantly more
pronounced than responses produced from a control TSST without
psychosocial challenges (H2).
2. Methods
2.1. Participants
The present study involves the analysis of participants in two in-
vestigations: A study on the effects of oxytocin on stress reactivity (Study
1) and a second project (PHEMORE study) examining individual dif-
ferences in stress reactivity (Study 2 and Study 3).
Study 1 included 52 female undergraduate students (Mean age =
19.9 ±1.8) participated in the Virtual TSST study. The majority (76.9%)
did not know the Second Life platform, some participants had heard of it
or seen it (21.1%), and only one participant had an account. The focus of
the larger project was to examine intranasal oxytocin effects on stress
reactivity and all participants were female (Riem et al., 2020). All par-
ticipants selected for the present analyses received a placebo nasal spray
(double-blind). Participants were screened for drug or alcohol abuse,
nasal problems, use of prescribed medication (except contraceptive
medication), psychiatric and neurological disorders, cardiovascular
diseases, and hypertension. Furthermore, participants who were preg-
nant, breastfed or had children were excluded from this study. The study
was approved by the Brabant Medical Ethics Committee
Data for the in-vivo TSST subset (Study 2) were retrieved from the
larger PHEMORE (Physiological and EMOtional Reactivity) study
(Kupper et al., 2020), which examined individual differences in reac-
tivity to mental stress among young adults. Data collection for this larger
study went on from January 2011 until June 2016 and was described
earlier in more detail (Kupper et al., 2020). Other individual differences
oriented papers published on a selection of the PHEMORE dataset either
are published (Duijndam et al., 2020), or are in the process of being
written. From the regular TSST dataset from 2015 and 2016 (closest in
time to the VR data collection), we drew a sample of 106 young adults
(36% male, age M =20.5 ±2.8), taking into consideration that the task
order in which they completed the experiment was similar as the VR
version (i.e. speech rst, then math). To test the rst hypothesis, we
selected the women from this sample (n =68). For the second hypoth-
esis, the full sample was used. Post-hoc power analysis for hypothesis 1
(most limited sample) showed that with an alpha of 0.05, we had suf-
cient statistical power (0.95) to prove a medium effect size (f =0.15/
Cohens d =0.40).
In 2016, 20 participants took part in a ‘control TSST(Study 3), as
part of the PHEMORE study, in which active stressor elements were
removed (aged M =21.2, SD =1.9, 40% female). Age did not differ
across studies, F(2, 137) =1.86, p =.159. This sample was only used to
test hypothesis 2. The Institutional Ethics Review Board approved the
PHEMORE study protocol (Study 2 and 3) and its amendments (protocol
number: EC-2011.01a). All participants gave informed consent before
participating and were debriefed afterwards.
2.2. Procedure
2.2.1. Study 1 Virtual TSST. The present data were collected in the GO-Lab of
Tilburg University, as part of a larger study on stress reactivity and
oxytocin (Riem et al., 2020). Participants were instructed to refrain from
smoking and coffee consumption on the day of the lab session and from
alcoholic beverages during the 24 h before testing. The VR-TSST pro-
tocol was highly similar to the protocol of the in vivo and control TSST
(see Fig. 1 and Appendix A). After signing informed consent, ECG
electrodes were attached and participants completed a 5-min rest
baseline measure, while watching a picture depicting a nature scene,
after which participants completed self-report anxiety measures (base-
line). Subsequently, the experimenter read out the instructions for the
TSST. The original protocol of the TSST was adapted such that partici-
pants were to remain seated throughout the entire procedure, because a
standing position or changes in posture may cause uctuations in blood
pressure (Olufsen et al., 2005). The VR-TSST was conducted using the
Second Life platform. Second Life is an online virtual world. Within
Second Life, individuals can interact with one another using virtual
representations of themselves (called avatars) through audio and chat
functions. Although this platform is public, the area that was used for the
VR-TSST was private and could not be accessed by anyone other than
those permitted by the principal investigator. Participants were
instructed to imagine applying for an internship position through the
Second Life platform. They were asked to prepare a 5-minute speech to
convince two professors that they would be the ideal candidate for the
position. The participant and the two professors were represented as
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
their own avatar in Second Life. After the speech, an additional math
task would provide information about the applicants working memory
capacity. A 5-minute preparatory period started after the instructions, in
which the experimenter retreated to the observation room. After 5 min,
the experimenter showed the participant the Second Life environment:
the TSST took place in a large auditorium with a virtual stage (See Ap-
pendix A; (Fallon et al., 2016)). Participants stood on the lower part of
the stage and looked at the two front seats, in which one male and one
female professor avatars were seated. The visual settings were zoomed
in, so that participants only saw the professors. The experimenter told
the participant that (s)he would briey contact the professors, to verify
that they had logged in successfully, left the lab room and announced
through a microphone that the professors were ready and would be in
contact in a minute.
The experimenter controlled the two professor avatars in Second
Life. Second Life allows pre-recorded audio messages to be uploaded and
then played by using the Sounds function. We recorded 36 Dutch and 36
English (for international students) messages that followed TSST pro-
tocols as described by Kupper et al. (Kupper et al., 2020) and used in
Study 2 (based on PHEMORE). The messages were recorded such that
the male and female professors talked in equal proportions. The rst
recordings included a brief introduction (Female: ‘Hi, can you hear me?,
Ok, we will begin the task shortly). The male professor then instructed
participants to start their speech. The following prompts were played if
participants were silent for 3 s: female: You still have some time, please
continue, male: You still have time, go on, male: Can you tell us something
about your strengths?, female: How would other students describe your
social skills?, and male: ‘Can you tell me something about your weak-
nesses?. In line with Fallon et al. (Fallon et al., 2016), the professor
avatars used the gestures ‘bored twice and ‘shrug once, at 1, 3 and 4
min into the speech respectively.
After 5 min, the professors gave the instructions for the math task.
The math task entailed subtracting 13 from a number, and then
repeatedly subtracting 13 from the remainder. Upon each mistake a new
starting number was given (e.g., ‘Thats incorrect, please start again, and
this time start from 1072). Additionally, the following prompts were used
once per participant: ‘At this point, youre making more errors compared
with other participants. Try to be more accurateand ‘You are being a little
slow compared to the other participants. Please try to speed up your answers.
After 5 min of performing the math task, the male avatar indicated
Please stop, your time is up. You can tell the experimenter now that you are
nished (instructed to raise hand). The remaining messages were recor-
ded to have a variety of options in case participants behaved unex-
pectedly (e.g., Are you OK to continue?, ‘I cannot comment on that, ‘Yes,
we can hear you).
After the math task, the experimenter returned to the laboratory
room and administered the second self-report anxiety measure. Partic-
ipants underwent a debrieng procedure at the end of the protocol. The
experimenter asked a series of increasingly suggestive questions to un-
cover whether the participant believed that she was talking to two
professors (i.e., What was your impression of the two professors?).
2.2.2. Study 2 In vivo TSST. Participants were instructed to refrain from
smoking and coffee consumption for 2 h before testing as well as not to
ingest more than three alcoholic beverages during the 24 h before
testing. After providing informed consent, participants were tted with
the cardiovascular measurement equipment at the GO-Lab. After a 10-
min resting period, during which we recorded a physiological base-
line, participants took part in a 5-min cognitive task not related to the
present analyses and a recovery period (5 min). The stress-inducing part
of the protocol then started using the Trier Social Stress Test (TSST),
followed by a 5-min recovery period. Participants lled out a second
questionnaire at the end of the protocol. The present paper reports on
the results pertaining to the 10-min resting phase and the responses to
the TSST.
We adapted the original protocol of the TSST in two ways. First,
similar to Study 1, we asked participants to remain seated throughout
the entire procedure (Olufsen et al., 2005). Second, instead of a job
interview, we asked participants to prepare (three-minute preparation
period) and give a speech on their own positive and negative social skills
(ve minutes), in front of a two-person audience. Previous research has
shown that the current procedure induces a signicant cardiovascular
stress response (Kupper et al., 2013). During the arithmetic task, par-
ticipants were asked to serially subtract a one-digit (e.g., 7) or two digit
(e.g., 13 or 19) numbers from four digit numbers verbally in the presence
of a socially evaluative audience. Comments were scripted and are
presented in Supplement 1.
2.2.3. Study 3 Control TSST. The control TSST was designed to be as close to
the original TSST as possible, while removing the key stress-inducing
elements, similar to the procedure described by Het et al. (Het et al.,
2009). After a 10-minute resting period, the participant was asked to
give a 5-minute speech about a movie, novel, a recent holiday trip, or
what they did during the weekend. The participants were informed that
there would be a 3-minute preparation period during which they should
think about the topic of the speech. After 3 min, the experimenter
entered the room and asked the participant to start their speech. The
experimenter stayed in the room, listening and nodding empathically. If
a participant stopped talking, the experimenter rst asked whether he/
she could tell some more, and if not, asked a question. After 5 min, the
experimenter asked the participant to stop talking and to start adding up
the number 5 starting at 0. This second task also lasted 5 min. The
Introducon & informed consent
Applicaon of physiological
equipment / preparing VR setup
Phase 1: Resng baseline (sing
Emoon report
Phase 2: Preparaon phase
Phase 3: Speech
Phase 4: Arithmec task
Emoon report
Introducon & informed consent
Applicaon of physiological
Phase 1: Resng baseline (sing
Emoon report
Phase 2: Preparaon phase
Phase 3: Speech
Phase 4: Arithmec task
Emoon report
+0 +10
-30 -35 +15 +20 +25 +27
+0 +10
-45 -65 +15 +20 +25 +27
Fig. 1. VR-TSST and in vivo TSST test procedure.
Note: Experimental procedure indicating the subsequent experimental phases
and their timing for respectively the VR (top panel) and the in vivo TSST
(lower panel).
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
experimenter wrote down the highest number reached. When the math
task was nished, participants were asked to sit and rest (recovery
period) for 5 min. The control TSST was performed in the same lab room
at GO-Lab as the in-vivo TSST and the VR-TSST, but all ‘stressingele-
ments of the TSST (committee of evaluators, performance pressure)
were removed. This procedure was expected to eliminate the main
effective factors of the TSST, namely the social evaluative threat and the
uncontrollability, consistent with the theory proposed by Dickerson and
Kemeny (2004).
2.3. Materials and instruments
2.3.1. Self-reported anxiety
Anxiety was measured after the resting baseline and right after the
TSST math task in all three studies. In the virtual TSST study (Study 1),
we used the Spielberger Trait-State Anxiety Inventory, State version
(STAI). The STAI includes 6 items that are scored on a 4-point Likert
scale (Marteau and Bekker, 1992). Participants were asked to complete
the STAI directly after the math task, and were asked to indicate how
they were feeling at that moment. We calculated a total score for STAI-S.
In Study 2 and 3, anxiety was measured using four 7-point Likert
scale items on anxiety. Participants were asked to indicate to what
extent they felt these emotions during the preceding task (after resting
baseline, and after the stress battery).
To enable comparison between the outcome measures of Study 1 and
Studies 2 and 3, we selected four items of the STAI (Study 1) that
matched the anxiety items of Study 2 and 3. In Study 2 and 3 the items
were ‘I feel at ease(reversed), ‘I am tense, ‘I feel anxious, ‘I am
stressed. Therefore, we selected the following items from the STAI in
Study 1: ‘I feel calm (reversed), ‘I am tense, ‘I feel upset and ‘I am
relaxed (reversed). The internal consistency of the four-item STAI in
Study 1 was
=0.73 at the resting baseline as well as after the math
task. The internal consistency of the derived four items anxiety scale in
Study 2 and 3 was
=0.82 at baseline and
=0.88 after the math task.
2.4. Electrocardiogram
In Study 1, the VR-TSST, heart period and heart rate variability were
derived from continuous ECG recordings made with the ECG100C
module and the Biopac MP150 system, and three hydrogel ECG elec-
trodes. Data were recorded at a sampling frequency of 2000 Hz. Data
processing was conducted in AcqKnowledge, version 4.4. Human ECG
complex boundaries were identied automatically and artifacts and
missed QRS peaks were identied and corrected manually. We calcu-
lated period averages for heart period (IBI), beats per minute (BPM), and
the average root mean square of successive differences (RMSSD), a
measure of cardiac parasympathetic activation, for each experiment
In Study 2 and 3, the PHEMORE (in vivo and control TSST studies),
the Vrije Universiteit Ambulatory Monitoring System (VU-AMS 4.6;
Vrije Universiteit Amsterdam, the Netherlands) was used to record a
continuous electrocardiogram (ECG) and impedance cardiogram (ICG)
at a frequency of 1000 Hz (Z0 at 250 Hz) (De Geus et al., 1995). Seven
non-woven, liquid gel AgCl electrodes (Kendall, Medcat, the
Netherlands) were used. The event button on the device was used to
indicate start and end times of the phases of the experimental protocol
and was operated by the test leader based on a stopwatch timing. VU-
AMS software was used to automatically detect all R-peaks in the
ECG, and all R-peak markers were visually checked and adjusted
manually when necessary. The signal was visually checked for artifacts
(e.g., premature atrial or ventricular contractions), which were removed
prior to scoring the ECG data. From the corrected ECG signal, we derived
IBI, HR, and RMSSD for each experiment phase. In all studies, RMSSD
was ln transformed because of skewed data distributions.
2.4.1. Belief in experimental VR setup
During the debrieng procedure of the VR-TSST, experimenters
rated the participants as ‘believer(participant believed the entire
experimental set-up), ‘doubter(e.g., participant questioned whether she
was talking to real people, whether the audience members were actual
professors), or ‘non-believer(participant was quite certain that pre-
recorded messages were used). Participants were additionally asked to
indicate how certain they were that they were talking to ‘real people
during the task (0 to 100%).
2.5. Statistical analysis
Descriptive statistics comprised means and standard deviations for
continuous variables, and frequencies for categorical variables. Pearson
Chi-square tests were used to compare the subset samples on categorical
sample characteristics (i.e., sex, smoking), while univariate analyses of
variance (ANOVA) was used to assess differences on continuous vari-
ables (i.e., age, BMI). Specic to the VR sample, repeated measures
ANOVA was used to assess the effect of believing the VR setup on the
emotional and physiological stress response. Specic to the two in vivo
samples, frequencies were calculated for adherence to health behavior
guidelines, and chi square tests gauged potential differences in these
percentages adherence.
The STAI-S (VR) and the emotion questionnaire (in vivo, control)
were summed for the resting baseline and the stress score. Because the
scale of the self-reported anxiety measures differed per study, the anx-
iety scores were rst standardized around their resting mean (SD). Then
the standardized scores were merged into one comparable score.
Data analysis for the physiological measures was as follows: As a
manipulation check, we rst examined the general reactions to the
virtual TSST by testing the within-person time effect in an otherwise
unadjusted analysis. The RMSSD variables were log-transformed,
because these variables had skewed distributions (Shapiro-Wilk <0.05).
To compare the effects of the three TSST types on anxiety change and
cardiovascular reactivity, a series of MIXED linear models were con-
ducted, with anxiety (2 time levels: rest - stress), inter-beat interval and
RMSSD (4 time levels) as outcome measures respectively. Time (Base-
line, Preparation, Speech, Math) was entered as the repeated measures
variable with an unstructured covariance matrix. For all models we
tested whether the models improved when adding a random intercept.
TSST type was entered as a xed factor, as was Time. For each Model, we
rst tested the main effects of TSST type and Time, and their interaction.
A signicant interaction would indicate that the TSST induced physio-
logical and emotional reactivity prole differed by TSST type. Then, we
tested the signicance of a random intercept, and nally sex was
included as a covariate in a second step because of its established effects
on emotion and physiology. We tested whether sex was a signicant
addition to the model using the AIC relative likelihood calculations. As
our hypothesis was about equivalence of the TSST versions, we per-
formed a TOST equivalence test for independent samples, based on
Welchs t-test (Lakens, 2017), when TSST type rendered a non-
signicant effect in the MIXED linear modeling. For this TOST equiva-
lence test, we need to set equivalence boundaries. We followed the
guidance of (Lakens, 2017), and chose the smallest effect sizes we had
statistical power for to detect as equivalence boundaries, i.e. Cohens
d of 0.40/0.40.
Two-sided p-values are reported and a two-sided p-value <.05 was
used for hypothesis testing. All analyses were conducted in SPSS
(version 24).
3. Results
3.1. Participants & manipulation check
A total of 178 participants participated in either the in vivo TSST (N
=106; 51 women), the VR-TSST (N =52), or the control TSST (N =20).
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
Participant characteristics are displayed in Table 1. There were signi-
cant sex differences between the three samples, while no signicant
differences were found in age and health behaviors. In the VR-TSST, 19
participants (39.6%) expressed some doubts about the experimental
setup, whereas fteen (31.3%) were rated as ‘believersand fourteen
(29.2%) as ‘non-believers(1 missing). Participants were on average
54.9% sure that they were talking to ‘real people, with SD =26.9 and
answers ranged from 0 to 100%. Believing the VR setup was unrelated to
the anxiety response to the VR-TSST (p =.484, partial
=0.03), but
was related to the physiological response (F
(6, 129) =3.05, p =.008,
=0.12; F
(6, 129) =1.41, p =.218, partial
with believers showing a larger heart rate response to stress than
There were no signicant differences between the virtual TSST versus
the in vivo TSST and control TSST (PHEMORE study) participants in their
adherence to the health behavior guidelines prior to study participation
(Ps between 0.32 and 0.57).
Examining the three data subsets separately, we rst established
whether the three versions of the TSST elicited the expected emotional
and physiological responses. With respect to anxious mood, we found a
signicant response to the VR-TSST (F(1, 50) =161.59, p <.001; partial
=0.76) and the in vivo TSST (F(1, 105) =238.17, p <.001; partial
=0.69), while there was no response in the control TSST (F(1,19) =
1.39, p =.25; partial
=0.07). Results also showed that all versions of
the TSST elicited signicant changes in heart period (F
(3, 144) =
85.77, p <.001, partial
=0.64; F
in vivo
(3, 312) =131.73, p <.001,
=0.56, F
(3, 51) =14.86, p <.001, partial
Repeated contrast analysis showed that all subsequent time points
signicantly differed from each other (p <.001). The VR-TSST (F(3,
144) =18.03, p <.001; partial
=0.27) and the in vivo TSST (F(2.4,
247.9) =30.28, p <.001; partial
=0.23) also elicited signicant
reductions in RMSSD, while the control TSST did not (F(3, 51) =1.69, p
=.18; partial
=0.09). Contrast analysis showed that while for the VR-
TSST preparation and speech were not signicantly different from each
other (p =.78), the other time points were (p <.001). For the in vivo
TSST all subsequent time points differed signicantly (p <.05).
3.2. Comparing the TSST versions
3.2.1. Anxious mood
The mixed linear model with two levels of anxious mood as an
outcome measure, a random intercept (see online results supplement for
modeling results), two main effects (Time, TSST type) and their inter-
action, showed that the emotional response to the VR-TSST was not
different from the emotional response to the in vivo TSST (F (1,119) =
0.216, p =.643; H1). The response size was 2.17 (se =0.17) stan-
dardized units in the VR-TSST, 2.05 (se =0.17) standardized units in the
in vivo TSST and 0.034 (se =0.24) in the control TSST (Fig. 2). The
equivalence test (TOST) indicated that the observed effect size for
anxiety reactivity (d =0.09) was signicantly within the equivalent
bounds of d = − 0.40 and d =0.40 (t(114.95) = − 1.71, p =.045), which
leads to the conclusion that for anxiety reactivity the VR-TSST is
equivalent to the in vivo TSST.
Using the sample for hypothesis 2 (i.e. men and women, without the
VR-TSST participants), the control TSST did not show an anxiety
response (Time effect: F(1,20) =1.45, p =.243). The in vivo TSST
induced a signicantly more pronounced anxiety response than the
control TSST (Time by TSST version: F(1, 126) =36.65; p <.001; H2).
There was a signicant main effect of sex, with women scoring on
average 0.41 standardized units higher at rest and stress than their male
counterparts (F(1,126) =5.00, p =.027). Adding sex to the model did
not affect the effect of TSST version (while sex was relevant to the
3.2.2. Physiology
Fig. 3 displays the physiological responses to the three versions of the
TSST. None of the models included a random intercept, as these models
provided a worse t to the data (Online Results supplement). To test
hypothesis 1 (VR-TSST not being different from in vivo TSST), mixed
linear modeling with IBI (i.e. heart period) as an outcome measure
showed a signicant interaction between time and TSST type, indicating
that the heart period response to the TSST differed per TSST version (F
(3; 117) =9.22, p <.001). Residuals were normally distributed. The in
vivo TSST induced a larger heart period reduction than the VR-TSST
(Fig. 3). Custom hypothesis testing for the difference in heart period
response between the VR-TSST with the in vivo TSST (H1) revealed that
the heart period response deviated during rest (i.e., the VR-TSST par-
ticipants were more relaxed; ΔIBI = − 52.76; t = − 2.68, p =.008), and
during the math stressor (ΔIBI = − 73.80; t = − 3.47, p =.001), with the
heart period being shorter (i.e. higher heart rate) in the in vivo TSST
(Fig. 3). The VR-TSST IBI response was equivalent for the preparation (t
= − 0.43, p =.669) and speech periods (t = − 1.23, p =.222).
For the second hypothesis (the in vivo TSST shows larger responses
than the control TSST), mixed linear modeling showed that the IBI
response differed in level between the in vivo and control TSST (F(1,
124) =4.81, p =.03), and that the prole over time differed in some
respects (F(3, 124) =2.34, p =.077). Custom hypothesis testing of the
interaction effect showed that in particular the prole of the IBI response
differed from the control prole in two aspects: the change from rest to
preparation (t =1.70, p =.091) and the response to the math task (t =
2.64, p =.009). Adding sex as a covariate, though a relevant addition to
the model (Online results supplement), did not result in a signicant
alteration of the results.
3.2.3. RMSSD
The mixed linear modeling with RMSSD as outcome measure showed
an interaction between time and TSST type (F(3, 133.98) =3.32, p =
Table 1
Sample characteristics.
(N =52)
In vivo TSST
(N =106)
Control TSST
(N =20)
N(%) or mean ±
N(%) or mean
N(%) or mean ±
52 (100%) 68 (64%) 8 (40%)
Age (years) 19.9 ±1.8 20.5 ±2.8 21.2 ±1.9 .701
12% (6) 15% (16) 20% (4) .644
BMI (kg/m
) 22.7 ±4.5 22.0 ±3.3 22.5 ±3.0 .496
Note: results are presented as % (n), unless otherwise indicated. Column pro-
portions were compared with the Fisher exact test. A subscript letter (a, b, c)
attached to the percentages indicates whether samples are all different from
each other, or that one sample stood out (a, b).
Fig. 2. Emotional response to the TSST stratied by TSST type.
Note: This gure shows the standardized mean (se) level of anxious mood for
the three TSST types during rest and during stress.
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
.022), indicating that the version of TSST signicantly affected the
RMSSD response prole. Custom hypothesis testing for the effects of this
interaction showed that this was in particular the case for the speech
response (t = − 2.17, p =.032) and the math response (t = − 3.69, p <
.001), with the in vivo TSST inducing more parasympathetic withdrawal
(Fig. 3).
With respect to the second hypothesis, Fig. 3 (bottom right gure in
comparison to upper right gure) shows the RMSSD prole for the
control group is lying in between the VR-TSST and the in vivo TSST
response. What is remarkable, is that the control TSST participants
overall show less parasympathetic activation, also in rest. Mixed linear
modeling showed that the RMSSD response in the control TSST was
equivalent to the in vivo TSST (F(1, 120.49) =1.93, p =.129). Adding
sex to the model as a covariate, though a relevant contribution to the
model (online results supplement), did not change the effect of Time by
TSST type. Sex was a non-signicant covariate (p =.23).
4. Discussion
The present study examined whether a VR version of the TSST poses
a viable alternative to the contemporary face-to-face TSST performed in
vivo regarding the emotional and autonomic cardiac response. Overall,
the results indicate that the emotional responses to the VR and in vivo
TSST were equivalent and both versions elicited higher responses than
the control TSST. There were signicant differences between TSST
versions regarding the autonomic cardiac response, with less para-
sympathetic withdrawal and a smaller heart period stress response in the
VR-TSST compared to the in vivo TSST. With respect to the second hy-
pothesis, the heart period stress response was signicantly larger than in
the control TSST, while the parasympathetic withdrawal was equiva-
lent. Together, these ndings suggest that the VR-TSST elicits similar
levels of negative affect, but less autonomic nervous system activation
than the standard in vivo TSST.
Previous studies employing a VR-TSST have shown signicant
emotional (Fallon et al., 2016), neuroendocrine (Fallon et al., 2016;
Jonsson et al., 2010; Ruiz et al., 2010) and cardiovascular (Jonsson
et al., 2010; Kotlyar et al., 2008) responses, suggestive of successful
production of the acute stress response. However, these studies did not
make a direct comparison between responses to a VR type stress test
with in vivo tests. A few previous studies have made a direct comparison
regarding emotional, neuroendocrine, and cardiovascular responses
(Kelly et al., 2007; Kothgassner et al., 2016; Shiban et al., 2016; Zimmer
et al., 2019), and all of these studies used a head mounted display for VR
presentation. With respect to the emotional stress response, our ndings
showed equal efciency in producing an emotional (i.e. anxiety) stress
response to the VR- and in vivo TSST. This is consistent with previous
Rest Prep Speech Math
Interbeat interval (ms)
Rest Prep Speech Math
Ln RMSSD (ln ms)
Rest Prep Speech Math
Interbeat interval (ms)
Rest Prep Speech Math
Ln RMSSD (ln ms)
Control TSST
Fig. 3. Physiological TSST response proles stratied by TSST type.
Note: Black lines represent the VR-TSST response prole. Solid gray line represent the response prole to the in vivo TSST, while dashed gray lines indicate the control
TSST response prole. Prep =preparation period, ln =natural log; ms =milliseconds, TSST =Trier Social Stress Test. Error bars represent ±1 SEM. * indicates
signicant contrast in interaction between time and TSST type (H1).
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
work showing no differences in perception of stressfulness, appraisal of
stress, or responses of anxiety between VR and in vivo TSSTs (Kelly et al.,
2007; Kothgassner et al., 2016; Shiban et al., 2016; Zimmer et al., 2019).
Differences do exist between studies with respect to the compara-
bility of the autonomic cardiac response. Our VR-TSST produced a
smaller heart period response, particularly during math, and less para-
sympathetic withdrawal compared to the in vivo TSST (the VR math task
may not have been challenging enough, which is discussed later in this
article). One prior study that directly compared VR-TSST with in vivo
TSST also showed an equivalent parasympathetic withdrawal (Koth-
gassner et al., 2016). Our ndings concur with the recent study of
Zimmer and colleagues reporting lower heart rate responses in the VR-
TSST condition, as compared to in vivo (Zimmer et al., 2019). Howev-
er, our ndings are not in line with other immersive VR vs. in vivo
comparison studies that have shown no differences in cardiovascular
reactivity between conditions (Kothgassner et al., 2016; Shiban et al.,
2016). In addition, given the potential role of the level of experienced
immersion, it is of note that Kothgassner and colleagues used a group
audience in their study, which may have inuenced their results as well
(Kothgassner et al., 2016). Increases in heart rate may be considered as
an indirect measure of task engagement (Seery, 2011). The reduced
capacity to mount a heart rate/period response observed in the current
study may be associated with the level of task engagement, but also with
the believability of the task. Zimmer et al., who also found a slightly
attenuated heart rate response to the VR-TSST (Zimmer et al., 2019),
suggested the TSST may be difcult to replicate in a virtual environment
due to its conceptualization as a socially evaluated and uncontrollable
performance stressor. It is of note that the anticipation response, which
is a private, passive response, prior to the active performance tasks was
similar in the VR-TSST and the in vivo TSST. The social evaluation and
negative feedback during the active performance stressors may be less
believable in VR. Our own ndings showed that individuals who
believed the experimental set-up showed increased heart rate responses
in the VR setting compared to others who believed the VR setting to a
lesser extent or not at all. This suggests that improving the believability
of the VR-TSST may also affect its effectiveness. Engagement with the
tasks at hand is also an important determinant of the responses to the in
vivo TSST (Seery, 2011), which makes believability also an important
aim in in vivo tasks. Future studies may want to examine whether making
participants believe in the experimental set-up may be one way to
further increase the effectiveness of VR-TSSTs, possibly even to the level
of in vivo TSST. Improvements to the VR-TSST could be achieved by
recording more voice messages that can be used to better, and more
exibly, simulate conversations between the participant and avatars.
Believability of the VR-TSST may also be improved by increasing the
level of immersion into the virtual task by making the visual images
more realistic than the current avatars. A recent meta-analysis showed
that immersive VR-TSSTs are more effective in inducing a cortisol
response, compared to non-immersive TSSTs, such as the currently used
Second-life screen version (Helminen et al., 2019). However, in
immersive TSSTs participants may realize that they are not actually
presenting in front of a real audience, but for programmed avatars,
which may set limits to effective stress induction. Moreover, head
mounted displays and CAVE environments may cause nausea and
simulation sickness in some participants (Pan and Hamilton, 2018).
These observations indicate that the level of immersion, believability of
the VR setting, and task engagement all may be important moderators of
the physiological response to a virtual stress task. It is important to
quantify their role in VR-TSST reactivity in future research.
It is also unclear if the physical presence of an (evaluative) audience
contributes to physiological reactivity in a VR-TSST, regardless of the
social evaluative threat and negative feedback. Dickerson et al. (2008)
found that negative social evaluation, but not mere social presence,
elicits a neuroendocrine response to a laboratory stressor. Our data are
in accordance in this respect, as in the control TSST the social evaluative
aspect was absent (though there was social presence) and emotional and
heart rate responses to the control TSST were attenuated. Additionally,
it has been shown in previous research that in the in vivo TSST, social
evaluation and audience size do matter. Anxiety, cortisol and autonomic
activation all have shown increased reactivity when the task had a so-
cially evaluative character. Moreover, physiological reactivity increased
in parallel with increasing audience size (Bosch et al., 2009). While our
VR-TSST had a two-person audience, physiological responses were
smaller than those of the in vivo TSST. Using a larger audience thus may
also increase response sizes.
Considering our ndings, the math task of the current VR-TSST could
be improved. The math task was substantially less stressful (i.e. less
physiological arousal) than the in vivo TSST. Most likely, this may be
attributed to differences in the negative feedback from evaluators (i.e.
number and timing exibility of interruptions, facial expression, and
tone of voice) and the associated social evaluative threat experienced by
the participants. Social evaluative threat is most likely to occur when
failure or poor performance could reveal lack of a valued trait or ability.
It is a key contributor to the physiological stress response in the TSST
(Dickerson and Kemeny, 2004). The current VR math task can thus be
improved by intensifying and more exibly applying the negative
feedback (gestures and comments) from evaluators. Examining the
scripted text of evaluators in the in vivo TSST and the VR-TSST, it is
evident that the instruction of the math task in the in vivo TSST already
contained more evaluative primers. Furthermore, the comments during
the performance were politer and nicer (i.e., little slower, please try
to, ) than the in vivo TSST. These are clear improvements that need to
be made to the VR math task.
The results of the current study should be viewed in light of several
limitations and strengths. We did not randomize participants into any of
the three TSST arms, but rather used separate samples of studies that
were executed in the same lab, with a similar TSST overall design,
though there were slight protocol variations. Because of this merge, we
also needed to standardize the scale of the anxiety responses of the in
vivo/control TSST study around their baseline mean. It should be noted
that differences in the tools to assess anxiety may have introduced bias.
The equipment to record the physiological measures also differed be-
tween the two studies, but it is unlikely to have affected the heart rate
and RMSSD ndings. In addition, while the in vivo TSST had a control
TSST counterpart, there was no control condition for the VR-TSST,
which would be a suggestion for future research. Because of the over-
all study design, the VR-TSST only was performed in women, while the
other two TSST protocols were performed in both women and men.
Since our VR-TSST only included women, we cannot conclusively say
the TSST responses were equivalent for men and women, regardless of
TSST type. Future studies examining sex differences will be important.
We did not have any performance measures (e.g. score on the math test),
to compare between the VR-TSST and the in vivo TSST, which may
provide some more detail. Nevertheless, the in vivo TSST elicited a
stronger physiological response. The difference in physiological
response may be explained by a more lenient math test protocol in the
VR-TSST, and VR-related issues discussed above. Another limitation is
that there was no a priori power analysis (convenience comparison), and
statistical analyses were not adjusted for multiple testing. However,
given the sample size, strict corrections of the alpha level were not
possible. Finally, because the VR-TSST participants were in the placebo
group of a larger trial, the placebo administration could have led to
attenuated responses when participants thought they were given
oxytocin. We tested this in a post-hoc analysis, and no differences were
found, which adds condence to our ndings. Strengths of the study
included the relatively large sample size, the combined assessment of
emotional and physiological reactivity, and the inclusion of sex as a
In conclusion, the present ndings demonstrate that social evalua-
tive stress induced in a screen-based VR setting produced similar
emotional, and somewhat attenuated autonomic cardiovascular re-
sponses as compared to in vivo. We recommend intensifying the social-
M.A. Fallon et al.
International Journal of Psychophysiology 161 (2021) 27–34
evaluative threat and time pressure during the math task by altering and
maximizing interaction in SecondLife, and increasing audience size,
which would be expected to lead to larger physiological responses.
Moreover, our ndings indicate that belief in the experimental-set up
results in a more effective stress induction. Thus, the credibility of the
experimental set-up of VR-TSSTs may be one important, but often
neglected, moderating factor that could increase the effectiveness of VR-
Data availability
The datasets analyzed during the current study are available from the
corresponding author on reasonable request.
Study 1 was sponsored by the Tilburg University Alumni Fund, the
Department of Medical and Clinical Psychology, and the Center of
Research on Psychological and Somatic disorders, Tilburg University,
The Netherlands. The authors declare no conicts of interest.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
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M.A. Fallon et al.
... We also agree with the idea mentioned in [54] by M.A. Fallon and colleagues, who argue that virtual reality, in addition to collecting data from a neural network, allows one to determine the emotional state of a person as well as his psychophysiological load. At the same time, a properly constructed research design will allow us not only to solve the problems of assessing a person's fall in a three-dimensional environment, but also to additionally train him in the balance pose and other physiological exercises [55]. ...
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... Therefore, we conclude that participants in our study considered the two virtual agents as a convincing social-evaluative threat, which explains the increased HPA reactivity to the VR-TSST. A recent study [4] underlines that believability affects the effectiveness of VR-TSST, as it reports that participants who believed the VR-TSST setting showed increased HR levels. Another explanation is that in our sample most participants reported to have a considerable technical expertise (mean of 4.23 to 4.30 across groups on a 5-point Likert-Scale); this could particularly help counteract the increase in stress reactivity due to the novelty of the virtual environment as discussed by . ...
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Background Although the Trier Social Stress Test (TSST) constitutes a valid paradigm for social stress induction, less is known about the effects of a virtual reality (VR) TSST on short- and long-term hypothalamic-pituitary-adrenal (HPA) axis and sympathetic-adreno-medullar (SAM) axis responses. Hence, this study set out to evaluate reactivity and habituation of self-reported stress and HPA and SAM reactivity in a real TSST and VR-TSST when compared to a placebo TSST. Method Sixty-eight healthy young adults (50% female) were randomly assigned to either a real TSST, a VR-TSST, or a placebo TSST, all of which were conducted three times (one day and one week post initial exposure). Social presence, self-reported stress, salivary cortisol, heart rate (HR), and heart rate variability (HRV) were analyzed using ANOVAs and multilevel models. Findings On the first exposure, both the real and VR-TSST showed significantly stronger cortisol and cardiovascular responses than the placebo. On the second visit, the cortisol response was still significantly high—and the HRV response low—for the real and VR-TSST. The third visit resulted in HR, HRV, and cortisol responses comparable to the placebo group. Furthermore, the real TSST induced more self-reported stress than the placebo on all three visits, the VR-TSST only on the first two visits. Social presence was stable across conditions and had no association with stress markers. Conclusion These findings imply that the replicability of stress exposures at shorter intervals seems problematic for the traditional TSST, and especially for the VR-TSST.
We investigated affective touch as a new pathway to passively mitigate in-the-moment anxiety. While existing mobile interventions offer great promises for health and well-being, they typically focus on achieving long-term effects such as shifting behaviors. As such, most mobile interventions are not applicable to provide immediate help in acute conditions -- when a user experiences a high anxiety level during ongoing events (e.g., completing high-stake tasks or mitigating interpersonal conflicts). A few works have developed passive interventions that are effective in-the-moment by leveraging breathing regulations and biofeedback. In this paper, we drew on neuroscientific findings on affective touch, the slow stroking on hairy skin that can elicit innate pleasantness and evaluated affective touch as a mobile health intervention. To induce affective touch, we first engineered a wearable device that renders a soft stroking sensation on the user's forearm. Then, we conducted a between-group experiment, in which participants underwent high-stress situations with/without receiving affective touch and post-experiment interviews, with 24 participants. Our results showed that participants who received affective touch experienced lower state anxiety and the same physiological stress response level compared to the control group participants. We also found that affective touch facilitated emotion regulation by rendering pleasantness, providing emotional support, and shifting attention. Finally, we discussed the immediate effect of affective touch on anxiety and physiological stress, the benefits of affective touch as a passive intervention, and the implementation considerations to use affective touch in just-in-time systems.
Social support is associated with mental well-being and favorable therapy outcomes. As autonomy-connectedness, the capacity for self-governance in interpersonal context, may affect reliance on others, we investigated whether stress-modulating effects of social support are moderated by autonomy-connectedness. Ninety-seven undergraduates completed measures on autonomy-connectedness and trait social anxiety, and attended a laboratory session with a friend (support) or alone (control). All underwent a virtual Trier Social Stress Test and completed anxiety, cortisol and heart rate (variability) measures. Preregistered analyses revealed that social support reduced anxiety reactivity and delayed heart rate variability decreases, but not heart rate. Contrary to hypotheses, autonomy-connectedness did not predict stress-reactivity or interact with condition. Exploratory analyses suggested effects of social support on cortisol reactivity and indicated that reported support quality varied by trait anxiety and self-awareness. Our findings underline the stress-modulating effects of social support and suggest that social support can benefit individuals with varying levels of autonomy-connectedness.
Functional lateralization relates to a natural asymmetry in the dominance right or left body side, and is a fundamental principle of the brain. The hemispheres of the brain control the contralateral body side, and show subtle, yet striking, anatomical asymmetries and functional lateralization. Innovative technologies, including Virtual Reality (VR), are entering the areas of experimental research, modeling and simulation related to the study of lateralization, with new perspectives of different applications in modern medical practice. Researchers/ clinicians note that there are fewer VR studies with healthy participants, and which are important in evaluating/ interpreting clinical outcomes, and testing the usefulness, limitations, and sensitivity of VR. The presented influence of the domination of upper/ lower limbs on the performance of VR exercises was studied in healthy right-handed adults. Virtual testing sessions were performed independently with both/ dominant/ non-dominant hands, and the similar VR sessions were conduced on a Wii Balance Board (WBB) with the choice of body side, at different levels of the difficulty. The obtained results are consistent with other studies which show that cognitive-motor training in VR with the WBB platform is a very sensitive and promising tool for recognizing/ assessing functional asymmetries of the right-left body side not only in disturbed lateralization, but also in the test training of healthy subjects.
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Oxytocin is considered a biological mechanism underlying stress-protective effects of positive social interactions. It is assumed to underlie the women-specific tend-and-befriend response to stress, although few studies have tested this assertion with female samples. The aim of the present study was, therefore, to test whether oxytocin enhances stress-protective effects of social support during stress in women, taking into account the moderating role of childhood adversity. The sample consisted of 180 female undergraduate students who had reported on experiences of childhood abuse and how often their mother used love withdrawal as an insensitive disciplinary strategy. Women participated in a virtual version of the Trier Social Stress Test (TSST) and were randomly assigned to receive 24 IU oxytocin or a placebo and to receive support or no support from a female friend (sub-groups N = 45). Results showed that oxytocin reduced heart rate variability during the TSST in participants who received support, possibly indicating that oxytocin increases attention and stimulates a challenge motivational state in the presence of a friend. In addition, we found that, in the presence of a friend, oxytocin reduced state anxiety levels and cortisol levels after the TSST, but only in women with higher levels of adverse childhood experiences. Our findings may indicate that oxytocin is a neurobiological means to attain and benefit from social support under stressful circumstances, which may be particularly adaptive for women with a history of adversity. Thus, oxytocin may function as motivator for affiliative disposition during stress exposure in women with a history of childhood adversity. Results should be replicated in clinical samples.
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As virtual reality (VR) technology and systems become more commercially available and accessible, more and more psychologists are starting to integrate VR as part of their methods. This approach offers major advantages in experimental control, reproducibility, and ecological validity, but also has limitations and hidden pitfalls which may distract the novice user. This study aimed to guide the psychologist into the novel world of VR, reviewing available instrumentation and mapping the landscape of possible systems. We use examples of state-of-the-art research to describe challenges which research is now solving, including embodiment, uncanny valley, simulation sickness, presence, ethics, and experimental design. Finally, we propose that the biggest challenge for the field would be to build a fully interactive virtual human who can pass a VR Turing test – and that this could only be achieved if psychologists, VR technologists, and AI researchers work together.
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Scientists should be able to provide support for the absence of a meaningful effect. Currently, researchers often incorrectly conclude an effect is absent based a nonsignificant result. A widely recommended approach within a frequentist framework is to test for equivalence. In equivalence tests, such as the two one-sided tests (TOST) procedure discussed in this article, an upper and lower equivalence bound is specified based on the smallest effect size of interest. The TOST procedure can be used to statistically reject the presence of effects large enough to be considered worthwhile. This practical primer with accompanying spreadsheet and R package enables psychologists to easily perform equivalence tests (and power analyses) by setting equivalence bounds based on standardized effect sizes and provides recommendations to prespecify equivalence bounds. Extending your statistical tool kit with equivalence tests is an easy way to improve your statistical and theoretical inferences.
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Social support and grief education can ameliorate mental and physical health risks in widow(er)s. However, barriers often prevent older individuals from attending support groups. This controlled pilot study examined the feasibility and acceptability of an online, real-time, interactive virtual reality (VR) support group for widow(er)s, and assessed the preliminary efficacy of the VR support group for improving psychosocial outcomes and sleep quality compared to an active control grief education website. Thirty widow(er)s (Mage = 67.0, SD = 11.0) participated in an 8-week VR support group or accessed a grief education website. Participants completed self-report measures of depression, grief intensity, grief cognitions, yearning, loneliness, perceived stress and sleep quality at three time points. Participant attrition and self-report indicated that both interventions were feasible and acceptable. Both groups showed significant improvements in grief severity, grief cognitions, yearning, loneliness, perceived stress, and global sleep quality across study time points. However, only widow(er)s in the VR support group showed a significant improvement in depression across time. This study demonstrates the feasibility, acceptability and preliminary efficacy of an accessible and low-cost online support format for widow(er)s.
Objectives: Individual differences in long-term cardiovascular disease risk are related to physiological responses to psychological stress. However, little is known about specific physiological response profiles in young adults that may set the stage for long-term increased cardiovascular disease risk. We investigated individual differences in profiles of resting cardiovascular physiology and stress reactivity, combining parasympathetic, sympathetic, and hemodynamic measures. Methods: Participants (N=744, 71% women, mean age=20.1±2.4 years) underwent the Trier Social Stress Test (TSST), while blood pressure (SBP, DBP), electrocardiograms (IBI), and impedance cardiograms (PEP, LVET) were recorded. RSA was derived from the combination of the ECG and the ICG. Three-step Latent Profile Analysis (LPA) was performed on resting and reactivity values to derive clusters of individual physiological profiles. We also explored demographic and health behavioral correlates of the observed latent clusters. Results: For resting physiology, LPA revealed five different resting physiology profiles, which were related to sex, usual physical activity levels and body mass index. Five cardiovascular stress reactivity profiles were identified: a reciprocal/moderate stress response (Cr1; 29%), and clusters characterized by high blood pressure reactivity (Cr2: 22%), high vagal withdrawal (Cr3; 22%), autonomic co-activation (SNS and PNS) (Cr4; 13%), and overall high reactivity (Cr5; 12%). Men were more likely to belong to the high reactivity (Cr5) cluster, while women were more likely to have autonomic co-activation (Cr4). Conclusion: We identified five cardiovascular physiological reactivity profiles, with individuals displaying generalized hyper-reactivity, predominant vagal withdrawal, autonomic co-activation, or blood pressure-specific hyper-reactivity. Longitudinal studies are needed to determine whether these profiles are useful in early detection of individuals at high risk of cardiovascular disease.
Background: There are large individual differences in dealing with everyday social stress. Therefore, we investigated the association of social inhibition (and its facets) with the emotional and physiological responses to the Trier Social Stress Test (TSST). Methods: Undergraduate students (N = 312) completed the 15-item Social Inhibition Questionnaire (SIQ15) and participated in the TSST, while emotional and cardiovascular stress responses were recorded. We examined the effect of social inhibition across time with repeated-measures ANCOVAs. Findings: During social stress (and recovery), social inhibition was associated with increased negative mood reactivity (especially the behavioral inhibition facet) and heightened sympathetic activation (especially the social withdrawal and interpersonal sensitivity). Physiological stress reactivity seems to be mostly α-adrenergic in women, and also β-adrenergic in men. Conclusions: Emotional and physiological stress responses are associated with individual differences in social inhibition. This warrants more research on mechanisms that underlie the relations between social inhibition, stress and health.
Background Maladaptive responses to stressors can lead to poor physical and psychological health outcomes. Laboratory studies of stress induction commonly use the Trier Social Stress Test (TSST). The TSST has been shown to reliably induce a stress response, most commonly measured via cortisol reactivity. Recently, researchers have used virtual environment versions of the TSST (V-TSST) in place of the traditional TSST. The V-TSST has many advantages over the traditional TSST, including increased standardization and use of fewer resources, but V-TSST has yet to be quantitatively reviewed and compared to the traditional TSST. This review aims to quantifying the effectiveness of V-TSST with a meta-analysis of cortisol response effects and identify potential moderating variables that are more likely to induce a cortisol response with V-TSST. Methods Literature searches were conducted including the key words Trier Social Stress Test, TSST, and virtual reality. Thirteen studies were included in this meta-analysis after meeting the inclusion criteria of utilizing a V-TSST and having cortisol measurements at baseline and peak stress to assess cortisol reactivity. The standardized mean gain effect size was used. Results and discussion There was a medium average effect size (ESsg = 0.65) across all studies for increase in cortisol from baseline to peak measurement. Significant moderating effects were seen for participant age, sex, and level of immersivity of the virtual environment. Studies in which participants were under 25 years old, or all male, showed greater effect sizes for cortisol reactivity. Virtual environments that were more immersive also evidenced greater effect sizes. Although the V-TSST is effective at inducing psychosocial stress, the magnitude of this response is less than the traditional TSST. Based on these results, recommendations for future research are provided.
In recent years, virtual reality (VR) technology has found its way into nearly all fields of psychology. Previous studies indicated that virtual reality adaptations of the TSST are less potent in stimulating HPA-axis responses, with lower salivary cortisol responses recorded as compared to the in-vivo TSST. (TSST-IV). In the present experiment we tested the stress-induction potential of a refined version of the TSST-VR using a fully orthogonal experimental design in which ninety-three healthy males were either assigned to the TSST condition or a corresponding control condition in a real or virtual environment. We found a significant increase of endocrine, autonomic and self-reported stress markers in both stress conditions. Notably, we found a robust rise in salivary cortisol to the TSST-VR comparable to that observed in the TSST-IV. Despite subtle differences in response between virtual and in vivo settings, we conclude that VR adaptations of in-vivo stressors have the potential to induce real physiological and subjective reactions.
Background: The Trier Social Stress Test (TSST) is one of the most widely used laboratory stress tests. Exposure to this psychosocial stressor has been shown to stimulate an acute cortisol stress response in the majority of healthy individuals, while deviations from the typical pattern, i.e., cortisol reactivity dysfunctions have been linked to an ever-increasing number of negative health outcomes. However, significant variability between labs exists in strength of observed cortisol responses in healthy individuals. This variability raises the question of how to distinguish across labs between cortisol stress response patterns that reflect health risk from those that are due to methodological differences. Thus, we propose a systematic review and meta-analysis that aims at quantifying the effects of methodological variation in study and TSST protocol elements on cortisol stress responses in healthy individuals. Methods: Literature searches were conducted using standard databases for English language with key words including Trier Social Stress Test, TSST, Cortisol, and Laboratory Stressor among others. 186 studies met our inclusion criteria of healthy human participants without systemic immunological or endocrine dysfunction and provided sufficient information to compute a total of 237 sub-sample effect sizes. Results and discussion: With regard to study protocol variations that may risk confounding baseline cortisol values and thus influence subsequent reactivity measures, meta-analytical examination revealed that acclimation periods pre-TSST below 30 or perhaps even 15min may suffice, at least as long as no interfering activities, i.e., questionnaires, are taking place during that timeframe. Assessing the effects of TSST protocol variations on cortisol response strength, several observations are noteworthy. First, shortening speech preparation time did not change cortisol responses in any way, nor did including questionnaires during that period show an effect. As such, our findings suggest that speech preparation time is one TSST element that can be used to reduce the burden for participants as well as laboratory logistics. Secondly, having an all female panel and instructing panel members to show negative instead of neutral behavior towards the participants both were associated with considerably reduced cortisol stress response strengths. Thirdly, several variables of interest, such as content of the speech task or gender match between active panel member and participant, were problematic to evaluate due to the large number of studies not reporting those details. This calls for future studies to report more details regarding potentially relevant protocol specifications.
The Trier Social Stress Test (TSST) is considered a reliable paradigm for inducing psychosocial stress. Virtual reality (VR) has successfully been applied to ensure a greater degree of efficiency and standardization in the TSST. Studies using the TSST in VR (VR-TSST) have reported significant stress reactions, with subjective and peripheral physiological reactions comparable to those in response to the in vivo TSST and with lower cortisol reactions. The current study examined whether an additional virtual competitive factor triggers larger stress responses than a standard VR-TSST. Forty-five male participants were randomly assigned to either in vivo TSST, VR-TSST (VR) or VR-TSST with a virtual competitor (VR +). A significant increase of self-reported stress, electrodermal activity, and heart rate indicated a pronounced stress reaction with no differences between groups. For salivary cortisol, however, responder rates differed significantly between groups, with in vivo participants showing overall higher response rates (86%) than participants of both VR groups (VR: 33%, VR +: 47%). In contrast, participants of both VR groups judged the task significantly more challenging than did in vivo TSST participants. In sum, our results indicate successful stress induction in all experimental conditions, and a marked dissociation of salivary cortisol levels on the one hand, and the physiological and psychological stress reactions on the other hand. The competitive scenario did not significantly enhance stress reactions. VR technology may serve as a standardized tool for inducing social stress in experimental settings, but further research is needed to clarify why the stress reaction as assessed by cortisol differs from peripheral and subjective stress reactions in VR.