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168
Articles
Ángel Ernesto Luquetta López
Universidad Estatal de Milagro, Ecuador
aluquettal@unemi.edu.ec
ORCID https://orcid.org/0009-0009-4630-8100
Cristian Javier Varela de la Hoz
Universidad estatal de Milagro, Ecuador
cvarelad2@unemi.edu.ec
ORCID https://orcid.org/0009-0003-5136-8622
Steven Arturo Torres Burgos
Universidad estatal de Milagro, Ecuador
storresb5@unemi.edu.ec
ORCID https://orcid.org/0000-0001-9299-3254
Abstract: Introduction: sedentary behavior and
long sitting periods in the classroom affect
students' attention, behavior and coexistence,
whereas active breaks are a brief, low-cost strategy
to introduce movement during lessons. Objective:
to assess the incidence of an active-breaks program
on selective attention, behavior and school
coexistence among secondary education students.
Materials and methods: a quasi-experimental
design with two groups and pre- and post-
measurements was used over eight weeks. Two
hundred tenth- and eleventh-grade students
participated and were assigned to an experimental
group and a control group. Selective attention was
assessed with a cancellation test, behavior with a
difficulties questionnaire, and coexistence with a
school-coexistence scale. Analyses of covariance,
mixed analyses of variance, effect sizes with
confidence intervals and power analysis were
applied. Results: the experimental group showed
significantly greater improvements than the
control group in the three variables, with
significant group-by-time interactions and
moderate effect sizes. Improved attention and
reduced behavioral difficulties were associated
with better coexistence. Conclusions: the results,
derived from simulated data for methodological
purposes, suggest that active breaks could
favorably affect selective attention, behavior and
school coexistence, although studies with empirical
data are required to confirm these trends.
Keywords: Active breaks; Selective attention;
Behavior; School coexistence; Physical activity.
Active breaks, selective attention, behavior and coexistence in secondary
education students
Ángel Ernesto Luquetta López
1
; Cristian Javier Varela de la Hoz
2
& Steven Arturo Torres Burgos
3
RIAF. International Journal of Physical Activity
Universidad de Guayaquil, Ecuador
Frequency: Semi-annual
Vol. 4, N°. 2, 2026
revista.riaf@ug.edu.ec
Received: June 13th, 2026
Approved: July 15
th
, 2026
Published: July 25
th
, 2026
URL: https://revistas.ug.edu.ec/index.php/riaf
DOI: https://doi.org/10.53591/riaf.v4i2.3373
Authors publishing in RIAF acknowledge and accept the following
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RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
169
Introduction
Regular physical activity promotes health and cognitive development during adolescence, a stage in
which most students do not achieve recommended levels of movement. The World Health Organization
recommends at least sixty minutes daily of moderate-to-vigorous physical activity for individuals aged
five to seventeen years (Bull et al., 2020); however, a high proportion of adolescents are insufficiently
active and remain seated for much of the school day (van Sluijs et al., 2021; Aubert et al., 2022). Prolonged
sitting time in the classroom is associated with declines in attention and increases in off-task behaviours,
which impacts teaching and learning processes.
In this scenario, active breaks—defined as brief interruptions to class during which students engage
in physical activity for a few minutes—have been proposed as a simple, feasible and low-cost strategy to
break up sedentary behaviour and favour academic-cognitive performance (Ruhland & Lange, 2021;
Peiris et al., 2022). Evidence indicates that active breaks can improve students' attention, particularly
selective attention, as well as in-class behaviour, although results are heterogeneous depending on the
intensity, duration and type of activity (Infantes-Paniagua et al., 2021; Mazzoli et al., 2021).
With respect to cognition, various syntheses show acute and chronic effects of movement on
executive function and attention in children and adolescents (Shi et al., 2022; Sibbick et al., 2022), and
specifically regarding secondary education students, a recent review supports the incorporation of active
breaks to enhance cognition, although it notes that the evidence is limited and heterogeneous (Bertón et
al., 2025). Regarding behaviour, physical activity in the classroom increases time on task and reduces
disruptive behaviours (Heemskerk et al., 2023; Reyes-Amigo et al., 2025a), and recent reviews document
effects on self-regulation and in-class behaviour (Reyes-Amigo et al., 2025b; Robles-Campos et al., 2023).
The relational dimension is also relevant. Physical activity has been linked to improved social
relationships and reduced peer victimisation (Rusillo-Magdaleno et al., 2024), and school coexistence—
understood as the quality of interactions and peaceful conflict management—has intervention
programmes whose efficacy has been systematically reviewed, with greater support for emotional
education and sport-based approaches (Tapullima-Mori et al., 2024). Nevertheless, coexistence has rarely
been examined as a direct outcome of active breaks.
Despite growing interest, a gap persists in the state of knowledge. Most studies have concentrated on
primary education and isolated outcomes—primarily attentional or in-class behaviour—whereas
secondary education has received less attention and school coexistence has barely been integrated as an
outcome variable. Few studies articulate, within a single design, selective attention, behaviour and
coexistence in secondary education students.
Consequently, the present study aims to assess the incidence of an active-breaks programme on
selective attention, behaviour and school coexistence in secondary education students, as well as to
examine the relationship between these variables. The relevance of the proposal lies in offering a
replicable methodological model that integrates cognitive, behavioural and relational indicators around
an easily implementable school strategy.
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Materials and Methods
Study Design
A quasi-experimental design was adopted with
two non-equivalent groups—experimental and
control—and repeated measurements at two time
points, before and after the intervention, over a
duration of eight weeks. This approach was
selected for its feasibility in real school contexts,
where individual random assignment is not viable
and students are grouped in pre-existing classes;
consequently, assignment to conditions was
carried out by clusters (whole classes), preserving
the natural classroom organization and reducing
contamination between groups. The unit of
analysis was the student and the factorial design
was mixed, combining a between-subjects factor
(group: experimental vs. control) and a within-
subjects factor (time: pre- vs. post-measurement).
To minimize bias, measurements were
administered by evaluators blind to participants'
condition (blinded assessment), total instructional
time was kept constant across both groups, and
contextual variables such as session timing and
teacher characteristics were controlled where
possible. Study planning and reporting adhered to
recommendations for non-randomized research.
Participants
The reference population consisted of
secondary education students enrolled at the
Institución Educativa Departamental Nuestra
Señora del Carmen de Guamal, Magdalena,
Colombia. The research was conducted over an
eight-week period corresponding to a block of
the 2025-2026 academic year. The sample
included 200 students, aged between fifteen and
seventeen years, evenly distributed across an
experimental group (n = 100) and a control group
(n = 100); each group comprised 50 tenth-grade
and 50 eleventh-grade students, with a balanced
sex distribution. Group formation sought initial
equivalence in grade, age and sex composition, a
condition verified empirically and reported in the
results section.
Group formation sought initial equivalence in
grade, age and sex composition, a condition
verified empirically and reported in the results
section.
Inclusion criteria:
students enrolled in
secondary education, with student assent and
informed consent from the responsible guardian,
and without medical contraindication for light
physical activity.
Exclusion criteria:
medical conditions
preventing participation in active breaks,
attendance below eighty per cent of sessions, or
absence from any of the measurements. Sampling
is described as non-probabilistic convenience
sampling, with group assignment by clusters
(classes) to reduce contamination between
conditions.
Intervention: active-breaks program
The experimental group participated in a
structured active-breaks program integrated into
the regular school day over eight consecutive
weeks. Each break consisted of a three- to five-
minute movement segment, executed within the
classroom two to three times per school day,
without requiring relocation or specialized
materials. Sessions followed a standardized three-
phase sequence: (1) an activation phase, with brief
in-place movements, walking and joint mobility;
(2) a main phase, with coordination exercises,
gentle jumps, balance and rhythmic motor
patterns of light to moderate intensity; and (3) a
closing phase, with stretching and controlled
breathing to facilitate transition back to academic
tasks. Dosage—duration, frequency and
intensity—was grounded in the available
evidence on active breaks in school contexts
(Infantes-Paniagua et al., 2021; Peiris et al., 2022;
Ruhland & Lange, 2021).
Implementation was carried out by teaching
staff, previously trained in a formative session and
provided with scripts and illustrations of each
routine, in order to guarantee uniformity of
application. To control intervention fidelity, a
compliance register was used in which the
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completion and duration of each break were
recorded; only students with participation equal
to or exceeding eighty per cent of sessions were
included in the analysis. The control group
maintained their usual school day, with identical
class time and without structured active breaks,
so that the only systematic difference between
conditions was the incorporation of the
movement program.
Variables and instruments
Selective attention. This was assessed using a
cancellation test of attention and concentration,
recording a concentration index based on hits and
errors; higher scores indicate better attentional
performance. This type of test presents adequate
evidence of construct validity and internal
consistency (Bates & Lemay, 2004).
Operationally, the test consists of rapid scanning
of rows of similar characters in which the
participant must cancel only the target stimuli
within a limited time; from hits and omission and
commission errors, a concentration index is
derived, with higher scores reflecting greater
selective attention and inhibitory control. Its
application is brief, collective and objectively
scored.
Behavior. A strengths and difficulties
questionnaire was used, from which the total
difficulties score was obtained; lower values
reflect better behavior. The instrument is widely
used in research with child and adolescent
populations (Goodman, 1997). In its structure,
the questionnaire comprises twenty-five items
organized into five subscales—emotional
symptoms, conduct problems,
hyperactivity/inattention, peer problems and
prosocial behavior—; the sum of the first four
subscales constitutes the total difficulties score,
ranging from 0 to 40, with higher values
indicating greater behavioral difficulty.
School coexistence. A Likert-type school
coexistence scale was used, transformed to a 0–
100 scale, where higher scores indicate more
positive coexistence; the appropriateness of
assessing coexistence through structured
questionnaires has been documented in field
reviews (Tapullima-Mori et al., 2024). The scale
captures core dimensions of coexistence—quality
of interpersonal relationships, respect for norms
and peaceful conflict management—through
Likert-type response items that are averaged and
rescaled to a 0–100 range for ease of
interpretation; higher scores express more
positive coexistence.
Procedure
The study was organized into three phases. In
the baseline phase (week zero), the three
measurements—selective attention, behavior and
coexistence—were administered to all
participants in both groups during the same time
slot and under standardized conditions. During
the intervention phase (weeks one to eight), the
experimental group developed the active-breaks
program integrated into the school day, while the
control group maintained their usual school
routine. In the post-intervention phase (week
nine), measurements were repeated using the
same instruments, the same evaluators and the
same application conditions as in the baseline. To
reduce bias, evaluators were unaware of each
class's condition, the test administration order
remained constant, and data were coded
anonymously prior to analysis.
Sample size and statistical power
The sample size (N=200; n=100 per group) was
considered adequate to detect moderate-
magnitude effects. A sensitivity analysis indicates
that, with two groups, a significance level of 0.05
and power of 0.80, the design allows detection of
standardized differences from d ≈ 0.40, a value
lower than the effects expected according to the
literature. Statistical power attained (post hoc) for
each contrast is reported in the results section.
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Statistical analysis
Data management and cleaning were performed
using Microsoft Excel and statistical processing
using the R language and environment (version
4.4.1). Data organization and transformation
were carried out using the tidyverse ecosystem
(dplyr and tidyr packages), and descriptive
statistics—means, standard deviations and
intervals—were obtained with the psych package.
To ensure reproducibility, a random seed
(set.seed) was set before any resampling-based
procedures.
The inferential analytical plan comprised: (a)
verification of baseline equivalence between
groups using independent samples t-tests and chi-
square test for sex; (b) verification of normality
assumptions with the Shapiro-Wilk test
(shapiro.test function) and homogeneity of
variances with Levene's test (car package); (c) an
analysis of covariance (ANCOVA) on the post-
measurement, with the pre-measurement as
covariate, estimated with the car package (type III
sums of squares) and whose adjusted marginal
means and 95% confidence intervals were
obtained with the emmeans package; (d) a two-
factor mixed analysis of variance (group × time)
with the afex package (aov_ez function) and
partial eta squared; (e) paired and independent
samples t-tests—the latter with Welch's
correction in case of unequal variances—and,
when assumptions were not met, their non-
parametric equivalent (Wilcoxon tests); (f)
calculation of Cohen's d effect size and partial eta
squared with the effectsize package, with 95%
confidence intervals obtained by bootstrap
resampling (2000 repetitions) using the boot
package; (g) statistical power analysis—both a
priori sensitivity calculation and attained power—
with the pwr package; (h) moderation analysis,
evaluating group × grade and group × sex
interactions on change scores; (i) test-retest
stability, estimated by pre-post correlation in the
control group; and (j) Pearson correlations
between changes in the three variables, with their
variables, with their confidence intervals and
power, calculated with the correlation package.
Figures were produced with the ggplot2 package.
A significance level of 0.05 was set. As an
essential methodological limitation, it is reiterated
that the data are simulated, so the results illustrate
the analytical procedure and do not constitute
empirical evidence.
Results
Analyses were performed on all 200 simulated
cases, with no missing values. Presentation
follows a logical sequence: descriptive statistics
and changes; baseline equivalence and
assumptions; intervention effect via analysis of
covariance and mixed model; moderation
analysis; measurement reliability; and cross-
domain association.
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Descriptive statistics and pre-post changes
Table 1.
Descriptive statistics (mean and standard deviation) by group and time point. (N = 200).
Variable
Group
Pre M (SD)
Post M (SD)
Change (Δ)
Selective attention (d2 index)
Experimental
118.0 (33.1)
128.5 (35.6)
+10.5
Selective attention (d2 index)
Control
115.7 (32.1)
119.4 (33.1)
+3.8
Behavior (difficulties;
lower=better)
Experimental
13.4 (5.3)
11.1 (6.1)
-2.2
Behavior (difficulties;
lower=better)
Control
14.0 (5.1)
13.7 (5.8)
-0.3
School coexistence (0-100)
Experimental
67.0 (12.0)
71.8 (13.8)
+4.8
School coexistence (0-100)
Control
67.0 (11.6)
68.6 (13.0)
+1.7
Analysis of descriptive statistics shows a
clearly superior improvement in the experimental
group. In relative terms, this group increased
selective attention by approximately 8.9%
(compared to 3.3% in the control) and school
coexistence by 7.2% (compared to 2.5%), and
reduced behavioral difficulties by around 16%
(compared to 2% in the control; a reduction
indicates improvement). Within-group contrasts
using paired samples t-tests confirmed that, in the
experimental group, changes were statistically
significant across all three variables (all p <
0.001), with large effect sizes for attention
(Cohen's d = 1.00) and behavior (d = -0.88) and
moderate for coexistence (d = 0.75). In the
control group, by contrast, only attention and
coexistence showed significant changes, of small
magnitude (d = 0.38 and 0.32, respectively), while
the behavioral change did not reach significance
(d = -0.15; p = 0.143). This pattern anticipates the
differential effect formally confirmed in
subsequent inferential analyses.
After the intervention, the experimental group
increased the attention index by 10.5 points
compared to 3.8 for the control group; behavioral
difficulties decreased by 2.2 points compared to
0.3 (a decrease indicates improvement); and
coexistence increased by 4.8 points compared to
1.7. Figure 1 illustrates the evolution of the
means, and Figure 2 shows the complete
distributions using box plots.
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Figure 1. Means (with standard error) before and after the intervention, by group
Figura 2. Distributions (boxplots) pre and post by group
Baseline equivalence and assumption verification
Before the intervention, groups did not differ significantly on any variable, with trivial effect sizes, and
sex distribution was homogeneous (χ² = 0.18; p = 0.671), supporting initial comparability (Table 2).
Table 2.
Baseline equivalence between groups (pre-measurements).
Variable
M Exp.
M Control
t
p
d
Selective attention (d2 index)
118.0
115.7
0.51
0.611
0.07
Behavior (difficulties)
13.4
14.0
-0.90
0.369
0.13
School coexistence (0-100)
67.0
67.0
0.02
0.984
0.00
The Shapiro-Wilk test indicated normality of change scores for attention and coexistence (p > 0.05)
and a slight deviation in behavior for the experimental group; Levene's test showed homogeneity of
variances for attention and behavior, and unequal variances for coexistence (Table 3). Consequently,
between-group comparisons employed Welch's correction and main contrasts were complemented with
analysis of covariance; results were confirmed using non-parametric tests, with equivalent conclusions.
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Table 3.
Assumption verification on change scores
Variable
Shapiro p
(Exp.)
Shapiro p
(Ctrl.)
Levene p
Decision
Selective attention (d2)
0.511
0.430
0.659
Met
Behavior (SDQ)
0.048
0.095
0.207
Non-param.
School coexistence
0.715
0.416
0.018
Welch
Intervention effect: ANCOVA and mixed model
Analysis of covariance, adjusting post-measurement by baseline, confirmed a significant group effect
across all three variables, with more favourable adjusted means in the experimental group (Table 4).
Convergently, mixed analysis of variance evidenced significant group × time interactions, and change
scores differed between groups with moderate effect sizes, confidence intervals excluding zero, and high
statistical power (Table 5; Figure 3).
Table 4.
Analysis of covariance (post-measurement adjusted by baseline) and adjusted marginal means with
95% CI
Variable
F(1,197)
η²
partial
Adj. M Exp. [95% CI]
Adj. M Ctrl. [95%
CI]
Selective attention (d2)
21.57
0.099
127.4 [125.3-129.4]
120.6 [118.6-122.6]
Behavior (SDQ)
29.52
0.130
11.47 [11.00-11.95]
13.33 [12.85-13.80]
School coexistence
14.41
0.068
71.76 [70.62-72.90]
68.65 [67.51-69.79]
All ANCOVA effects were significant (p < 0.001 for attention and behavior; p < 0.001 for
coexistence), with partial eta squared values between 0.068 and 0.130, corresponding to medium-
magnitude effects.
Table 5.
Group × time interaction, between-group effect size with 95% CI and power
Variable
Interaction
F(1,198) [η²p]
Cohen's d [95%
CI]
Power
p
Selective attention (d2)
21.81 [0.099]
0.66 [0.39-0.96]
1.00
< 0.001
Behavior (SDQ)
30.44 [0.133]
-0.78 [-1.06--
0.51]
1.00
< 0.001
School coexistence
14.45 [0.068]
0.54 [0.27-0.82]
0.97
< 0.001
Figure 3. Between-group effect size (Cohen's d) with 95% confidence intervals
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Moderation analysis
The group × sex interaction was not significant
for any variable (all p > 0.26), so the effect was
homogeneous between male and female students.
The group × grade interaction was also not
significant for attention (p = 0.734) nor behavior
(p = 0.291), but did reach significance, with small
magnitude, for school coexistence (F=4.18;
p=0.042; η² partial=0.021), suggesting that the
effect on coexistence might vary slightly
according to grade. This nuance should be
interpreted with caution and verified in empirical
studies.
Measurement reliability
Test-retest stability, estimated by correlation
between pre- and post-measurements in the
control group, was high across all three variables
(attention r = 0.95; behaviour r = 0.92;
coexistence r = 0.92), indicating consistent
measurements and supporting that observed
changes in the experimental group are not due to
random instrument fluctuations.
Association between attention, behavior and
coexistence
In the experimental group, significant
associations were observed between changes in
the variables (Table 6; Figure 4). Improvement in
selective attention was associated with better
coexistence, and reduction in behavioral
difficulties was likewise associated with better
coexistence (negative coefficient, since a lower
difficulties score indicates better behavior). The
relationship between changes in attention and
behavior was weak and non-significant. The
correlation matrix (Figure 5) summarizes the
pattern of associations.
Table 6.
Pearson correlations between changes in variables (experimental group, n = 100)
Relationship between changes
r [95% CI]
p
Power
Δ selective attention – Δ coexistence
0.25 [0.06–0.43]
0.011
0.73
Δ behavior (difficulties) – Δ coexistence
-0.23 [-0.41—0.03]
0.022
0.64
Δ selective attention – Δ behavior
-0.12 [-0.31–0.08]
0.225
0.23
Figure 4. Scatter plots with regression line between changes in variables (experimental group).
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Discussion
The present study evaluated, through a
methodological model with simulated data, the
incidence of an active-breaks program on
selective attention, behavior and school
coexistence in secondary education students.
Simulated results showed significantly greater
improvements in the experimental group across
the three variables, with significant group-by-time
interaction effects, favorable adjusted means after
controlling for baseline measurement, moderate
effect sizes with precise confidence intervals, and
associations between improvement in attention
and behavior and better coexistence. These
findings must be interpreted as an illustration of
expected behavior under the study hypotheses,
and not as empirical evidence.
The direction of simulated results is consistent
with the available literature. Regarding selective
attention, the favorable effects agree with the
meta-analytic synthesis identifying benefits of
active breaks on student attention, especially
selective attention (Infantes-Paniagua et al.,
2021), and with evidence on the effects of
movement on executive function in children and
adolescents (Shi et al., 2022; Sibbick et al., 2022).
Particularly pertinent to the population studied, a
review focused on secondary school students
supports the incorporation of active breaks to
enhance cognition (Bertón et al., 2025).
Figure 5. Correlation matrix of changes (experimental group).
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Regarding behavior, the simulated reduction
in difficulties is congruent with studies reporting
increases in time on task and reduction of
disruptive behaviors following physical activity in
the classroom (Heemskerk et al., 2023; Reyes-
Amigo et al., 2025a), as well as with reviews on
the effects of active breaks on behavior and self-
regulation (Peiris et al., 2022; Reyes-Amigo et al.,
2025b; Robles-Campos et al., 2023). With respect
to school coexistence, the simulated
improvement aligns with evidence linking
physical activity with better peer relationships and
reduced victimization (Rusillo-Magdaleno et al.,
2024) and with the literature on coexistence
improvement programs (Tapullima-Mori et al.,
2024).
The observed associations between
improvement in attention and behavior and
better coexistence suggest, within the limits of the
model, that active breaks might affect cognitive,
behavioral and relational dimensions in an
integrated manner. A plausible explanation is that
reduction in sitting time and regulation of arousal
favor both attentional focus and self-control,
which in turn would facilitate more positive
interactions in the classroom. Nevertheless, an
alternative explanation is that the novelty and
enjoyment of the breaks, rather than the
movement itself, account for part of the changes,
which should be clarified in empirical studies with
mediation analysis.
From the standpoint of analytical robustness,
results were consistent across complementary
procedures: analysis of covariance, which
controls for baseline measurement, coincided
with the mixed model and with comparison of
change scores; effects remained after employing
Welch's correction for unequal variances and
non-parametric tests; effect size confidence
intervals were precise and attained statistical
power was high; moderation analysis did not
evidence differences by sex and only a small
interaction by grade for coexistence; and test-
retest stability was high.
Together, these elements illustrate the
methodological control required of quality
research, although their value remains conditional
on the simulated nature of the data.
Among the strengths of the approach are the
integration of three dimensions usually studied
separately, the focus on secondary education—
less represented in the literature—and the
application of an exhaustive and reproducible
analytical plan. As limitations, the most relevant
is that data are simulated, so conclusions cannot
be generalized to real populations; the quasi-
experimental design does not permit robust
causal inferences; the eight-week period does not
inform about sustainability of effects; and
coexistence measurement through self-report
may be subject to social desirability. Likewise,
implementation fidelity of active breaks and
teacher training condition results in real contexts
(Ruhland & Lange, 2021).
The implications of this model are primarily
methodological and pedagogical.
Methodologically, the study provides a replicable
template for articulating cognitive, behavioural
and relational indicators around a brief school
strategy. Pedagogically, it offers an easily
implementable intervention framework requiring
no specialized resources. Future research lines
should execute the protocol with empirical data,
employ cluster-randomized designs with
prolonged follow-up, incorporate objective
measures of physical activity and observed
behavior, and analyze the mechanisms linking
attention, behavior and coexistence. In summary,
the scope of this work is limited to demonstrating
the coherence of an analytical model; its
significance will depend on subsequent empirical
verification.
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179
Conclusions
In coherence with the stated objective, results
obtained from simulated data suggest that an
active-breaks program could favorably affect
selective attention, behavior and school
coexistence in secondary education students, with
improvements greater than those of the control
group, and that such improvements would tend
to be interrelated. These statements are
illustrative and cautious in nature, as they do not
derive from actual measurements.
Therefore, it is concluded that active breaks
constitute a promising and easily implementable
strategy to jointly favor attentional development,
behavioral regulation and coexistence in
secondary education, provided that their
adoption is accompanied by methodological
rigor, implementation fidelity and ethical
safeguards. Research with empirical data, robust
designs and prolonged follow-up is required to
confirm these trends and clarify the mechanisms
involved.
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Declaration of conflicts of interest: Through
this document, the authors of this article assume
the regulatory and normative provisions of the
RIAF Journal's publication policies and therefore
declare no conflicts of interest in this regard.
Authors' contributions:
Ángel Ernesto Luquetta López: Developed
the research methodology, designed the
diagnostic instruments and techniques, and
implemented the program in the experimental
group.
Cristian Javier Varela de la Hoz: Conducted
the bibliographic search and constructed
citations, references and theoretical
systematization of the study variables.
RIAF Journal ISSN: 2953-6693 Vol – 4 No. 2, July 2026
181
Steven Arturo Torres Burgos: Participated in
the review, analysis and decision-making in the
writing of the literature, theoretical
systematization of the study variables, application
of empirical instruments, and in the results and
conclusions of the research.