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Journal of Positive Psychology & Wellbeing http://journalppw.com
2022, Vol. 6, No. 1, 1810 – 1830 ISSN 2587-0130
© 2021 JPPW. All rights reserved
Effect of a Mindfulness intervention with virtual reality in adolescents
on Attention and working memory
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3
1 Academic Program of Psychology, Autonomous University of Nayarit, Tepic, Nayarit, México.
E-mail: aimee.arguero@uan.edu.mx https://orcid.org/0000-0002-3864-52990001,
2Area di Psicologia. Istituto Universitario Salesiano Venezia. Mestre, Italia.
E-mail: d.marchioro@iusve.it
3Universidad Autónoma de Aguascalientes, Aguascalientes, México.
E-mail: psic.ivan@live.com, http://orcid.org/0000-0003-2046-1421.
Abstract
Introduction: Mindfulness has proven to be a very valuable practice to improve people's attentional
and working memory capacities. These abilities evolve over time, but if they are properly trained, they
can reach greater potential, especially if this training is done during childhood and adolescence.
Adolescents do not always feel motivated to practice mindfulness, so the aim of this work consists in
proposing a mindfulness intervention through the use of a virtual reality headset that allows access to
mindfulness training in a way that is more attractive to them.
Method. An experimental design was used to evaluate the effect of a Mindfulness intervention with
virtual reality (MIVR) using the app TRIPP, in a sample of 47 adolescents (G1n= 25, G2n= 22; mean
age = 15.53; SD = .99; 57.44% female) trough The RehaCom Screening Test on Divided Attention
(DA) and Working Memory (WM), before (T1 = pretest), and 21 days after its implementation (T2 =
posttest).
Results: The results showed that there was a significant difference between the experimental and
control groups between measurements (T 2 T1), in terms of divided attention and working memory (p
<0.001), but not between woman and man, suggesting a significant improvement in 21 days of the
MIVR.
Discussion. This research corroborates and contributes to a better understanding of the direct effects on
Virtual Reality-Mindfulness interaction, also verifying that adherence to monitoring the process gives
evidence of the motivation acquired by adolescents.
Keywords: Mindfulness, Intervention, Tripp, Oculus Rift S, Virtual Reality, RehaCom, Attention,
Working Memory, Adolescence.
Introduction
Mindfulness implies full attention, a way of
focusing on the present moment, as a
psychological process it means focusing
attention on what is being done or feeling
(Vásquez-Dextre, 2016), this has been shown in
research, where it is observed how mindfulness
improves attention, memory, the emotional state
and its regulation (Basso, et al., 2019). In
children and adolescents, improvement in
attention and other executive functions has been
confirmed (Dunning, et al., 2019).
In this sense, it is known that adolescents need
to feel motivated to learn (Limón & Carretero,
1995) and that these experiences are attractive or
pleasant, especially linked to technologies
(Garitaonandia, et al., 2005), so doing
mindfulness, turns out to be more attractive, in
addition to the fact that training children and
adolescents in any aspect at an early age is better
than waiting until they reach adulthood (Limón
& Carretero, 1995).
According to the American Psychological
Association, mindfulness meditation, also called
mindfulness, is defined as the training of
attention to achieve a mental state of calm
1811 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
concentration and positive emotions. In this, two
parts are considered: attention and acceptance.
The first seeks to tune into experiences to focus
on what is happening in the present moment,
achieving it through the direction of breathing,
thoughts, physical sensations, and feelings. The
second, acceptance, implies observing what is
being experienced without judging, that is,
instead of responding or reacting, those
emotions are allowed to pass. (APA, 2019).
The benefit of mindfulness is both psychic and
physical, it is used to deal with stress and other
difficult emotions such as anger and the lack of
control that derives from it. It helps the thoughts
to have more objectivity, to recognize the states
that alter or influence those thoughts. This
means that instead of repressing or reacting to
negative emotions, which are the two common
states of emotional regulation, mindfulness
helps to 'be with' the emotions and separate the
rawness of those emotions, along with the
feelings and thoughts that surround (Naik, et al.,
2013).
Creswell (2017) described an evaluation article
on mindfulness-based interventions for health,
cognition, affectivity, and interpersonal
relationships, as well as applications targeting
settings and populations (work, school,
military), the mechanisms neurobiological and
psychological among other aspects. This
research found that mindfulness interventions
improve outcomes in multiple domains ranging
from chronic pain to addictions, for example.
In a review article of randomized controlled
trials regarding the effects of mindfulness-based
interventions on cognition and mental health in
children and adolescents, it was found that all
trials found significant improvements in
mindfulness versus controls in categories such
as executive functioning, attention, depression,
anxiety, stress, and negative behaviors
(Dunning, et al., 2019).
Virtual reality (VR) is understood as a man-
machine interface using computer-generated
simulators, it is also a synthetic experience
where physical reality is substituted to achieve
an immersive interaction between the user and
the world (Pérez, 2011).
Heras and Villarreal (2004) described that this
technology dates back to 1960, but its use was
until the end of the 20th century, maturing in
components such as hardware, software,
applications, and content. Its use has been
directed mainly at education, art, entertainment,
dissemination of science and technology,
museums, products, storytelling, and even in the
military industry. The expression virtual reality
goes back to some discussions about the context
of technologies among technologists such as J.
Lanier, t. Nelson, M. Krueger, and J. Walker
raised the practical problem of relating more
humanely and naturally between a user and the
interface (Castañares, 2011).
The first applications of VR in psychology were
focused on exposure techniques used in phobias,
but also in psychic and psychomotor
rehabilitation, although there were also
antecedents that were aimed at general
psychological treatment and anxiety in students
(Gutiérrez, 2002).
VR as a tool in general and specialized care
services, as well as in psychotherapy, has been
sustained as an effective strategy (Riva, 2005).
Comparing them with traditional treatments, VR
has advantages such as the protected
environment for the patient and the re-
experiencing of a truly felt situation. Evidence
of effectiveness in anxiety, eating, and sexual
disorders has also been recovered (Botella, et al.,
2004). Even so, much research is lacking to
support this effectiveness in mental health (
Gregg & Tarrier, 2007). In an experiment to
investigate the influences of VR on dissociation,
mindfulness, and self-efficacy, the results
showed that participants who were immersed in
a VR system for 20 minutes increased
dissociation and a significant increase in
mindfulness after being immersed in simulation
(Mondellini, et al., 2021). Also, in studies where
VR was used for attentional and memory
improvement in adults, it was shown to be more
efficient than computerized (Climent, et al.,
2021). Virtuality offers an innovative way to
research, to live experiences, and to train
(Argüero-Fonseca, et al., 2021; Modrego-
Alarcón, et al., 2021), adolescents are more
attracted, manages to link these two practices,
mindfulness and virtual reality, to improve
attentional aspects and working memory.
Adolescence is defined by The World Health
Organization (WHO) as the stage between the
ages of 10 and 19. They normally divide it into
two phases; early adolescence from 12 to 14
years old and late adolescence from 15 to 19
years old (WHO, 2022).
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1812
© 2021 JPPW. All rights reserved
In each of these stages, there are physiological
changes (stimulation and functioning of the
organs by hormones, female and male),
structural (anatomical), psychological
(integration of personality and identity), and
adaptation to cultural and/or social changes
(SSA, 2015).
On the other side, the United Nations Children's
Fund (UNICEF, 2015) points out that both
adolescence and youth are periods of
opportunities and changes during which
adolescents and young people develop their
capacities to learn, experiment, use critical
thinking, express their creative freedom and
participate in social and political processes, so
ensuring the full development of these capacities
must be a common priority for all societies.
Adolescents have been a subject open to
research and an object of concern for social
scientists, educators, parents, and civic and
political institutions, but so are their research
strategies and methods, both qualitative and
quantitative. This is how the modern treatment
of adolescence is a field of study for
anthropology, psychology, developmental
biology, sociology, and history (Lozano, 2014).
In the field of psychology there are many books
and studies, for example, in Aguirre (1994) this
stage was studied from the cultural, biological,
gender identity, corporeality, sexuality,
affective development, cognitive development,
the experience of the socio-family group,
socialization, relationships with their parents,
ideology and values, access to work, among
others. At the neuropsychological level,
adolescents have been studied from various
angles, they have gone from a clinical
perspective as psychiatric patients (Allott, et al.,
2013) also around their emotions (Orón, 2014)
or from their executive functions in relation to
their sexual behavior (Morais, et al., 2016) and
their eating behavior (Herbrich, et al., 2019) to
their relationship between anxiety and attention,
working memory among other tasks in the
performance of its operation (Jarros, et al.,
2017).
Working memory is the system that maintains a
limited set of representations for immediate use
in cognition, it is a central part of human
cognition (Ricker, et al., 2018). The term
"working memory" evolved from the earlier
concept of short-term memory, and the two are
still sometimes used interchangeably. But it is
safe to say that the popularity of the concept of
working memory owes much to neurobiological
studies that seem to suggest that it may depend
on one or more specific anatomical locations.
There are many theories that address this
concept such as Cowan's integrated process
theory, Daneman and Carpenter's individual
difference-based theories, Jonides' mind and
brain, computational models (Baddeley, 2012).
Working memory is one of the cognitive
constructs with the greatest influence and
attention it has received in recent years. It can be
defined as the ability to temporarily keep
information active for use in different cognitive
activities such as understanding or thinking
(Pelegrina, et al., 2016).
Working memory is essential for learning,
language understanding, reasoning, problema-
solving, planning, and categorization. It is even
difficult to think of any complex cognitive task
that does not require the use of working memory
(Ramos, et al., 2007).
The development of the concept of a single
memory system to a system of more components
in working memory has been very
advantageous, both in theoretical and applied
research. In this way, the importance of working
memory is clarified by translating it as a general
system of cognitive control and executive
processing that indicates behavior and that
implies interactions between the different
processes of the mind such as attention,
perception, motivation, and memory (López,
2011).
In relation to attention, it facilitates objective
processing during perceptual and post
perceptual stages, and functionally dissociated
processes have been implicated in maintaining
different types of information in working
memory (AWH, et al., 2006).
As said before, adolescents do not always feel
motivated to practice mindfulness, so the aim of
this work consists in proposing a mindfulness
intervention through the use of a virtual reality
headset that allows access to mindfulness
training in a way that is more attractive to them,
evidencing the favorable effects on attention and
working memory of the participants.
1813 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
Method
Study design
In the present study, was used an experimental
study of two groups repeated measures design
(T1 =pretest, T2 = posttest) (Roberts & Ilardi,
2003) to evaluate the effect of a Mindfulness
intervention with virtual reality (MIVR) on
divided attention (DA) and working memory
(WM).
Participants
Volunteer adolescents, summoned through a
social network (Facebook), from the city of
Tepic, Nayarit, Mexico. Individuals who were
interested in participating received detailed
study information and a written informed
consent form for the tutors.
Inclusion criteria.
Adolescents aged between 14 and 17 years old,
who had the permission of their tutor, who was
not used to using virtual reality (VR) or the
Oculus Rift S headset, who had not previously
practiced mindfulness, who did not report vision
problems, with Level B2 Cambridge English.
Exclusion criteria.
People who did not agree to participate in the
study or those who did not complete the two
consecutive measurements in time (T1 =pretest,
and T2= posttest).
Study setting
The intervention was carried out in a
psychotherapy office owned by the researcher,
located in the city of Tepic, Nayarit, México.
Procedure
The adolescents were individually scheduled
together with their tutor to evaluate divided
attention and working memory through the
RehaCom software, with a pretest duration of 20
minutes. For the intervention, the participants
attended the appointment in groups of 5 people.
The headset was placed on them and later, after
5 minutes of habituation, the app whose guided
mindfulness meditation lasted 7 minutes was
started. In the end, they were allowed to stay 3
minutes of immersion. The intervention was
carried out from Monday to Saturday for 21
days. At the end of which, the participants were
individually called again for their second
evaluation.
Outcome’s variables
Measures of divided attention (DA) and working
memory (WM) were evaluated with the
RehaCom Screening Test, a well-identified
instrument used in previous research (Amonn, et
al., 2013; Flavia, et al., 2010; Zahraa, et al.,
2021). It consists of 9 modules for screening the
cognitive status of people with neurological
and/or psychiatric diseases but also is used in
healthy subjects.
For DA, the client has to solve a visual and an
auditive task-parallel simultaneously in one
trial. One trial contains 80 visual stimuli with
about 15% relevant stimuli as well as 160
auditive stimuli with approximately 10%
relevant stimuli. For a visual as well as an
auditive stimulus, the client has to push the same
button on the keyboard. Both tasks start at the
same time. (See Figure 1). For the Divided
Attention screening module, two Z-values are
calculated, Z-values 1 (Auditive divided
attention), the standard value is the number of
auditive omissions; meaning the number of
missed reactions to two consecutive, identical
acoustic stimuli. Z-values 2 (Visual divided
attention), the standard value is the number of
visual omissions; meaning: the number of
missed reactions to a relevant visual stimulus
(Hasomed, 2022).
Figure 1. Screening of Divided Attention
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1814
© 2021 JPPW. All rights reserved
Source: Hasomed, 2022
For WM, the screening is similar to the classic
Corsi-Block-Tapping. Individual dots
sequentially turn red and fade. The first
sequence consists of two random dots out of the
10 lighting up in a particular order. After the
sequence is presented, the patient must select the
same dots in the same order as they were
presented. Each sequence is new, meaning
sequences do not repeat the previous sequence.
If the patient selects a sequence of dots correctly,
the number of dots increases in the next
sequence. The task is to register and memorize
the presented sequence of dots lighting up. The
patient should try to memorize the sequence and
position of the red dots and to reproduce them.
The program is adaptive, adjusting the difficulty
according to the performance of the client. If the
patient makes a mistake, the degree of difficulty
is reduced. The screening ends after the patient
incorrectly reproduces two consecutive
sequences or after 7 minutes (See Figure 2). In
the Working Memory screening module, one Z-
value is calculated. Z-value: Memory span The
patient’s memory span is based on the highest
sequence length measured in number of dots,
reproduced without mistakes in position and
order. The memory span must be confirmed by
completing two consecutive sequences with the
same number of dots (Hasomed, 2022).
Figure 2. Screening of Working Memory
1815 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
Source: Hasomed, 2022
Tools
Oculus Rift S. The Oculus Rift S device is a
Head-mounted display (HMD), which is used to
project an immersive virtual reality in front of
the user and allows them to focus on the screen
without distractions. A magnetic sensor inside
the HMD detects the user’s head movement and
sends that information to the attached processor.
Consequently, the user turns his head; the
displayed graphics can reflect the changing
point of view, which allows an immersive
experience in virtual reality designed for video
games (Facebook, 2014).
TRIPP VR Meditation App. Include guided
meditations with immersive mindfulness
teachings. TRIPP® works with neuroscience
and psychiatric advisors to inform its product
development and design choices as well as
approaches on how to work effectively with
researchers and clinicians focused on the
category of digital therapeutics (Schrempf, et al.,
2021). It was used version 1.0.2744.2939 in
English (Tripp, 2022).
Statistical analyses
Were used three Mixed Model ANOVA, one for
DividedattentionAuditivePretest and
DividedattentionauditivePosttest by Group and
Sex; The second Mixed Model ANOVA for
DividedattentionvisualPretest and
DividedattentionvisualPosttest by Group and
Sex; a thord Mixed Model ANOVA for
WorkingMemoryPretest and
WorkingMemoryPosttest by Group and Sex.
Ethical considerations
This study is considered a minimal risk
investigation, in accordance with Article 17 of
the Mexican General Law of Health in Research
Matters for Health (Diario Oficial de la
Federacion, 1987), because it involved a
psychological procedure in human beings. The
authors based their application of moral rules
and professional codes of conduct according to
the recommendations for Conduct, Reports,
Edition, and Publication of Academic Papers in
Medical Journals (ICMJE, 2019).
Results
Mixed Model ANOVA 1
Introduction
A mixed model analysis of variance (ANOVA)
with one within-subjects factor and two
between-subjects factors was conducted to
determine whether significant differences exist
among DividedattentionAuditivePretest and
DividedattentionauditivePosttest between the
levels of Group and Sex.
Assumptions
Normality. The assumption of normality was
assessed by plotting the quantiles of the model
residuals against the quantiles of a Chi-square
distribution, also called a Q-Q scatterplot
(DeCarlo, 1997). For the assumption of
normality to be met, the quantiles of the
residuals must not strongly deviate from the
theoretical quantiles. Strong deviations could
indicate that the parameter estimates are
unreliable. Figure 3 presents a Q-Q scatterplot
of model residuals.
Figure 3
Q-Q scatterplot for normality of the residuals for the regression model.
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1816
© 2021 JPPW. All rights reserved
Homoscedasticity. Homoscedasticity was
evaluated by plotting the residuals against the
predicted values (Bates et al., 2014; Field, 2017;
Osborne & Walters, 2002). The assumption of
homoscedasticity is met if the points appear
randomly distributed with a mean of zero and no
apparent curvature. Figure 4 presents a
scatterplot of predicted values and model
residuals.
Figure 4
Residuals scatterplot testing homoscedasticity
Sphericity. The usual sphericity assumption
does not apply when there are only two repeated
measurements.
Multivariate Outliers. To identify influential
points in the residuals, Mahalanobis distances
were calculated and compared to a χ2
1817 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
distribution (Newton & Rudestam, 2012). An
outlier was defined as any Mahalanobis distance
that exceeds 13.82, the 0.999 quantile of a χ2
distribution with 2 degrees of freedom (Kline,
2015). There were 1 observations detected as
outliers.
Results
The results were examined based on an alpha of
.05. The main effect for Group was significant,
F(1, 43) = 7.40, p = .009, indicating that there
were significant differences in
DividedattentionAuditivePretest and
DividedattentionauditivePosttest between the
levels of Group. The main effect for Sex was not
significant, F(1, 43) = 0.95, p = .336, indicating
the levels of Sex were all similar for
DividedattentionAuditivePretest and
DividedattentionauditivePosttest. The main
effect for the within-subjects factor was
significant, F(1, 43) = 7.07, p = .011, indicating
there were significant differences between the
values of DividedattentionAuditivePretest and
DividedattentionauditivePosttest. The
interaction effect between the within-subjects
factor and Group was significant, F(1, 43) =
5.47, p = .024, indicating that the relationship
between DividedattentionAuditivePretest and
DividedattentionauditivePosttest differed
significantly between the levels of Group. The
interaction effect between the within-subjects
factor and Sex was not significant, F(1, 43) =
0.03, p = .867, indicating that the relationship
between DividedattentionAuditivePretest and
DividedattentionauditivePosttest was similar
between the levels of Sex. Table 1 presents the
ANOVA results.
Table 1
Mixed Model ANOVA Results
Source
df
SS
MS
F
p
ηp2
Between-Subjects
Group
1
6.78
6.78
7.40
.009
0.15
Sex
1
0.87
0.87
0.95
.336
0.02
Group:Sex
1
2.93
2.93
3.20
.081
0.07
Residuals
43
39.40
0.92
Within-Subjects
Within Factor
1
5.17
5.17
7.07
.011
0.14
Group:Within.Factor
1
4.00
4.00
5.47
.024
0.11
Sex:Within.Factor
1
0.02
0.02
0.03
.867
0.0007
Group:Sex:Within.Factor
1
0.10
0.10
0.14
.710
0.003
Residuals
43
31.40
0.73
Post-hoc. The mean contrasts utilized Tukey
comparisons based on an alpha of .05. Tukey
comparisons were used to test the differences in
the estimated marginal means for each
combination of between-subject and within-
subject effects.
Between Effects. For the Experimental category
of Group, DividedattentionAuditivePretest was
significantly less than
DividedattentionauditivePosttest, t(43) = -3.73,
p < .001. No other significant differences were
found for Group. For the Woman category of
Sex, DividedattentionAuditivePretest was
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1818
© 2021 JPPW. All rights reserved
significantly less than
DividedattentionauditivePosttest, t(43) = -2.19,
p = .034. No other significant differences were
found for Sex. Table 2 presents the marginal
means contrasts for the Mixed Model ANOVA.
Table 2
The Marginal Means Contrasts for each Combination of Within-Subject Variables for the Mixed
Model ANOVA
Contrast
Difference
SE
df
t
p
Group|Control
DividedattentionAuditivePretest -
DividedattentionauditivePosttest
-0.06
0.27
43
-
0.22
.830
Group|Experimental
DividedattentionAuditivePretest -
DividedattentionauditivePosttest
-0.90
0.24
43
-
3.73
<
.001
Sex|Man
DividedattentionAuditivePretest -
DividedattentionauditivePosttest
-0.45
0.28
43
-
1.63
.110
Sex|Woman
DividedattentionAuditivePretest -
DividedattentionauditivePosttest
-0.51
0.23
43
-
2.19
.034
Note. Tukey Comparisons were used to test the differences in estimated marginal means.
Between Effect Interactions. For the
combination of the Man category of Sex and the
Experimental category of Group,
DividedattentionAuditivePretest was
significantly less than
DividedattentionauditivePosttest, t(43) = -2.31,
p = .026. For the combination of the Woman
category of Sex and the Experimental category
of Group, DividedattentionAuditivePretest was
significantly less than
DividedattentionauditivePosttest, t(43) = -2.98,
p = .005. No other significant differences were
found for the interaction between Sex:Group.
Table 3 presents the marginal means contrasts
for each combination of the between effect
interactions and within-subjects factor.
Table 3
The Marginal Means Contrasts for each Combination of the Between-Subject Interactions and
Within-Subject Factor for the Mixed Model ANOVA
Contrast
Difference
SE
df
t
p
Sex|Man:Group|Control
DividedattentionAuditivePretest - DividedattentionauditivePosttest
-0.09
0.43
43
-0.22
.825
Sex|Woman:Group|Control
1819 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
DividedattentionAuditivePretest - DividedattentionauditivePosttest
-0.02
0.32
43
-0.06
.950
Sex|Man:Group|Experimental
DividedattentionAuditivePretest - DividedattentionauditivePosttest
-0.80
0.35
43
-2.31
.026
Sex|Woman:Group|Experimental
DividedattentionAuditivePretest - DividedattentionauditivePosttest
-1.00
0.34
43
-2.98
.005
Note. Tukey Comparisons were used to test the differences in estimated
marginal means.
Mixed Model ANOVA 2
Introduction
A mixed model analysis of variance (ANOVA)
with one within-subjects factor and two
between-subjects factors was conducted to
determine whether significant differences exist
among DividedattentionvisualPretest and
DividedattentionvisualPosttest between the
levels of Group and Sex.
Assumptions
Normality. The assumption of normality was
assessed by plotting the quantiles of the model
residuals against the quantiles of a Chi-square
distribution, also called a Q-Q scatterplot
(DeCarlo, 1997). For the assumption of
normality to be met, the quantiles of the
residuals must not strongly deviate from the
theoretical quantiles. Strong deviations could
indicate that the parameter estimates are
unreliable. Figure 5 presents a Q-Q scatterplot
of model residuals.
Figure 5
Q-Q scatterplot for normality of the residuals for the regression model.
Homoscedasticity. Homoscedasticity was
evaluated by plotting the residuals against the predicted values (Bates et al., 2014; Field, 2017;
Osborne & Walters, 2002). The assumption of
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1820
© 2021 JPPW. All rights reserved
homoscedasticity is met if the points appear
randomly distributed with a mean of zero and no
apparent curvature. Figure 6 presents a
scatterplot of predicted values and model
residuals.
Figure 6
Residuals scatterplot testing homoscedasticity
Sphericity. The usual sphericity assumption
does not apply when there are only two repeated
measurements.
Multivariate Outliers. To identify influential
points in the residuals, Mahalanobis distances
were calculated and compared to a χ2
distribution (Newton & Rudestam, 2012). An
outlier was defined as any Mahalanobis distance
that exceeds 13.82, the 0.999 quantile of a χ2
distribution with 2 degrees of freedom (Kline,
2015). There were no outliers detected in the
model.
Results
The results were examined based on an alpha of
.05. The main effect for Group was significant,
F(1, 43) = 11.27, p = .002, indicating that there
were significant differences in
DividedattentionvisualPretest and
DividedattentionvisualPosttest between the
levels of Group. The main effect for Sex was not
significant, F(1, 43) = 0.09, p = .771, indicating
the levels of Sex were all similar for
DividedattentionvisualPretest and
DividedattentionvisualPosttest. The interaction
effect between Group and Sex was not
significant F(1, 43) = 0.34, p = .563, indicating
there were no significant differences in
DividedattentionvisualPretest and
DividedattentionvisualPosttest for each factor
level combination of Group and Sex. The main
effect for the within-subjects factor was
significant, F(1, 43) = 41.40, p < .001, indicating
there were significant differences between the
values of DividedattentionvisualPretest and
DividedattentionvisualPosttest. The interaction
effect between the within-subjects factor and
Group was significant, F(1, 43) = 28.70, p <
.001, indicating that the relationship between
DividedattentionvisualPretest and
DividedattentionvisualPosttest differed
significantly between the levels of Group. The
interaction effect between the within-subjects
factor and Sex was not significant, F(1, 43) =
3.78, p = .058, indicating that the relationship
1821 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
between DividedattentionvisualPretest and
DividedattentionvisualPosttest was similar
between the levels of Sex. The interaction effect
between the within-subjects factor, Group, and
Sex was significant F(1, 43) = 4.19, p = .047,
indicating that the relationship differed
significantly between the factor level
combinations of Group and Sex. Table 4
presents the ANOVA results.
Table 4
Mixed Model ANOVA Results
Source
df
SS
MS
F
p
ηp2
Between-Subjects
Group
1
5.09
5.09
11.27
.002
0.21
Sex
1
0.04
0.04
0.09
.771
0.002
Group:Sex
1
0.15
0.15
0.34
.563
0.008
Residuals
43
19.41
0.45
Within-Subjects
Within Factor
1
1.59
1.59
41.40
< .001
0.49
Group:Within.Factor
1
1.10
1.10
28.70
< .001
0.40
Sex:Within.Factor
1
0.15
0.15
3.78
.058
0.08
Group:Sex:Within.Factor
1
0.16
0.16
4.19
.047
0.09
Residuals
43
1.65
0.04
Post-hoc. The mean contrasts utilized Tukey
comparisons based on an alpha of .05. Tukey
comparisons were used to test the differences in
the estimated marginal means for each
combination of between-subject and within-
subject effects.
Between Effects. For the Experimental category
of Group, DividedattentionvisualPretest was
significantly less than
DividedattentionvisualPosttest, t(43) = -8.80, p
< .001. No other significant differences were
found for Group. For the Man category of Sex,
DividedattentionvisualPretest was significantly
less than DividedattentionvisualPosttest, t(43) =
-5.48, p < .001. For the Woman category of Sex,
DividedattentionvisualPretest was significantly
less than DividedattentionvisualPosttest, t(43) =
-3.48, p = .001. Table 5 presents the marginal
means contrasts for the Mixed Model ANOVA.
Table 5
The Marginal Means Contrasts for each Combination of Within-Subject Variables for the Mixed
Model ANOVA
Contrast
Difference
SE
df
t
p
Group|Control
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1822
© 2021 JPPW. All rights reserved
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.04
0.06
43
-
0.73
.472
Group|Experimental
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.49
0.06
43
-
8.80
<
.001
Sex|Man
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.35
0.06
43
-
5.48
<
.001
Sex|Woman
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.19
0.05
43
-
3.48
.001
Note. Tukey Comparisons were used to test the differences in estimated marginal means.
Between Effect Interactions. For the
combination of the Experimental category of
Group and the Man category of Sex,
DividedattentionvisualPretest was significantly
less than DividedattentionvisualPosttest, t(43) =
-8.16, p < .001. For the combination of the
Experimental category of Group and the Woman
category of Sex, DividedattentionvisualPretest
was significantly less than
DividedattentionvisualPosttest, t(43) = -4.20, p
< .001. No other significant differences were
found for the interaction between Group:Sex.
Table 6 presents the marginal means contrasts
for each combination of the between effect
interactions and within-subjects factor.
Table 6
The Marginal Means Contrasts for each Combination of the Between-Subject Interactions and
Within-Subject Factor for the Mixed Model ANOVA
Contrast
Difference
SE
df
t
p
Group|Control:Sex|Man
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.04
0.10
43
-
0.41
.683
Group|Experimental:Sex|Man
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.65
0.08
43
-
8.16
<
.001
Group|Control:Sex|Woman
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.05
0.07
43
-
0.66
.514
Group|Experimental:Sex|Woman
DividedattentionvisualPretest -
DividedattentionvisualPosttest
-0.32
0.08
43
-
4.20
<
.001
1823 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
Note. Tukey Comparisons were used to test the differences in estimated marginal means.
Mixed Model ANOVA 3
Introduction
A mixed model analysis of variance (ANOVA)
with one within-subjects factor and two
between-subjects factors was conducted to
determine whether significant differences exist
among WorkingMemoryPretest and
WorkingMemoryPosttest between the levels of
Group and Sex.
Assumptions
Normality. The assumption of normality was
assessed by plotting the quantiles of the model
residuals against the quantiles of a Chi-square
distribution, also called a Q-Q scatterplot
(DeCarlo, 1997). For the assumption of
normality to be met, the quantiles of the
residuals must not strongly deviate from the
theoretical quantiles. Strong deviations could
indicate that the parameter estimates are
unreliable. Figure 7 presents a Q-Q scatterplot
of model residuals.
Figure 7
Q-Q scatterplot for normality of the residuals for the regression model.
Homoscedasticity. Homoscedasticity was
evaluated by plotting the residuals against the
predicted values (Bates et al., 2014; Field, 2017;
Osborne & Walters, 2002). The assumption of
homoscedasticity is met if the points appear
randomly distributed with a mean of zero and no
apparent curvature. Figure 8 presents a
scatterplot of predicted values and model
residuals.
Figure 8
Residuals scatterplot testing homoscedasticity
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1824
© 2021 JPPW. All rights reserved
Sphericity. The usual sphericity assumption
does not apply when there are only two repeated
measurements.
Multivariate Outliers. To identify influential
points in the residuals, Mahalanobis distances
were calculated and compared to a χ2
distribution (Newton & Rudestam, 2012). An
outlier was defined as any Mahalanobis distance
that exceeds 13.82, the 0.999 quantile of a χ2
distribution with 2 degrees of freedom (Kline,
2015). There were 1 observations detected as
outliers.
Results
The results were examined based on an alpha of
.05. The main effect for Group was not
significant, F(1, 43) = 1.20, p = .279, indicating
the levels of Group were all similar for
WorkingMemoryPretest and
WorkingMemoryPosttest. The main effect for
Sex was not significant, F(1, 43) = 0.96, p =
.333, indicating the levels of Sex were all similar
for WorkingMemoryPretest and
WorkingMemoryPosttest. The interaction effect
between Group and Sex was not significant F(1,
43) = 0.47, p = .498, indicating there were no
significant differences in
WorkingMemoryPretest and
WorkingMemoryPosttest for each factor level
combination of Group and Sex. The main effect
for the within-subjects factor was significant,
F(1, 43) = 89.95, p < .001, indicating there were
significant differences between the values of
WorkingMemoryPretest and
WorkingMemoryPosttest. The interaction effect
between the within-subjects factor and Group
was significant, F(1, 43) = 58.40, p < .001,
indicating that the relationship between
WorkingMemoryPretest and
WorkingMemoryPosttest differed significantly
between the levels of Group. The interaction
effect between the within-subjects factor and
Sex was not significant, F(1, 43) = 0.07, p =
.791, indicating that the relationship between
WorkingMemoryPretest and
WorkingMemoryPosttest was similar between
the levels of Sex. The interaction effect between
the within-subjects factor and Group:Sex was
not significant F(1, 43) = 0.01, p = .918,
indicating that the relationship between
WorkingMemoryPretest and
WorkingMemoryPosttest was similar between
the factor level combinations of Group and Sex.
Table 7 presents the ANOVA results.
Table 7
Mixed Model ANOVA Results
1825 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
Source
df
SS
MS
F
p
ηp2
Between-Subjects
Group
1
0.67
0.67
1.20
.279
0.03
Sex
1
0.53
0.53
0.96
.333
0.02
Group:Sex
1
0.26
0.26
0.47
.498
0.01
Residuals
43
23.95
0.56
Within-Subjects
Within Factor
1
3.50
3.50
89.95
< .001
0.68
Group:Within.Factor
1
2.28
2.28
58.40
< .001
0.58
Sex:Within.Factor
1
0.003
0.003
0.07
.791
0.002
Group:Sex:Within.Factor
1
0.0004
0.0004
0.01
.918
0.0002
Residuals
43
1.68
0.04
Post-hoc. The mean contrasts utilized Tukey
comparisons based on an alpha of .05. Tukey
comparisons were used to test the differences in
the estimated marginal means for each
combination of between-subject and within-
subject effects.
Between Effects. For the Experimental category
of Group, WorkingMemoryPretest was
significantly less than WorkingMemoryPosttest,
t(43) = -12.77, p < .001. No other significant
differences were found for Group. For the Man
category of Sex, WorkingMemoryPretest was
significantly less than WorkingMemoryPosttest,
t(43) = -6.03, p < .001. For the Woman category
of Sex, WorkingMemoryPretest was
significantly less than WorkingMemoryPosttest,
t(43) = -7.56, p < .001. Table 8 presents the
marginal means contrasts for the Mixed Model
ANOVA.
Table 8
The Marginal Means Contrasts for each Combination of Within-Subject Variables for the Mixed
Model ANOVA
Contrast
Difference
SE
df
t
p
Group|Control
WorkingMemoryPretest - WorkingMemoryPosttest
-0.08
0.06
43
-1.24
.221
Group|Experimental
WorkingMemoryPretest - WorkingMemoryPosttest
-0.71
0.06
43
-12.77
< .001
Sex|Man
WorkingMemoryPretest - WorkingMemoryPosttest
-0.38
0.06
43
-6.03
< .001
Sex|Woman
Aimée Argüero-Fonseca1, Davide María Marchioro2, Iván López-Beltrán3 1826
© 2021 JPPW. All rights reserved
WorkingMemoryPretest - WorkingMemoryPosttest
-0.41
0.05
43
-7.56
< .001
Note. Tukey Comparisons were used to test the differences in estimated marginal means.
Between Effect Interactions. For the
combination of the Experimental category of
Group and the Man category of Sex,
WorkingMemoryPretest was significantly less
than WorkingMemoryPosttest, t(43) = -8.67, p <
.001. For the combination of the Experimental
category of Group and the Woman category of
Sex, WorkingMemoryPretest was significantly
less than WorkingMemoryPosttest, t(43) = -
9.42, p < .001. No other significant differences
were found for the interaction between
Group:Sex. Table 9 presents the marginal means
contrasts for each combination of the between
effect interactions and within-subjects factor.
Table 9
The Marginal Means Contrasts for each Combination of the Between-Subject Interactions and
Within-Subject Factor for the Mixed Model ANOVA
Contrast
Difference
SE
df
t
p
Group|Control:Sex|Man
WorkingMemoryPretest - WorkingMemoryPosttest
-0.07
0.10
43
-0.71
.482
Group|Experimental:Sex|Man
WorkingMemoryPretest - WorkingMemoryPosttest
-0.70
0.08
43
-8.67
< .001
Group|Control:Sex|Woman
WorkingMemoryPretest - WorkingMemoryPosttest
-0.08
0.07
43
-1.12
.269
Group|Experimental:Sex|Woman
WorkingMemoryPretest - WorkingMemoryPosttest
-0.73
0.08
43
-9.42
< .001
Note. Tukey Comparisons were used to test the differences in estimated marginal means.
Conclusion and Discussion
The aim of this work consisted in proposing a
mindfulness intervention through the use of a
virtual reality headset that allows access to
mindfulness training in a way that is more
attractive to adolescents, evidencing the
favorable effects on attention and working
memory of the participants.
The results showed that there was a significant
difference between the experimental and control
groups between measurements (T 2 T1), in terms
of divided attention (auditive and visual) and
working memory (p <0.001), but there were no
differences between man and woman,
suggesting a significant improvement in 21 days
of MIVR.
The impact of virtual reality in the field of
education and technology, when used for
learning, can produce favorable effects on
cognitive abilities, by producing presence and a
stronger immersion experience (Budhwani, et
al., 2021; Parsons, et al., 2017; Blume, et al.,
2017), a tool that strengthens interventions of
any kind, especially mindfulness (Yuan, 2021;
Hillhouse, et al., 2021; Miller, et al., 2021). This
research corroborates and contributes to a better
understanding of the direct effects on this
Virtual Reality and mindfulness interaction, also
verifying that adherence to monitoring the
process gives evidence of the motivation
acquired by adolescents.
It could be interesting in a subsequent
investigation to compare this intervention
1827 Journal of Positive Psychology & Wellbeing
© 2021 JPPW. All rights reserved
against one that does not use virtual reality,
because although the effects on divided attention
and working memory could be verified, as a
second step, a comparative study could be
carried out that allows expanding the
intervention options in adolescents.
Funding
This work involves a project financed by the
patronage of the Autonomous University of
Nayarit, Mexico. Project No. 0000000007/21
Disclosure statement
The author(s) declared no potential conflicts of
interest with respect to the research.
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