EFFECTS OF LINEAR AND UNDULATING
RESISTANCE TRAINING PERIODIZATION ON
EXECUTIVE FUNCTIONS, PHYSICAL
ADAPTATIONS, AND PERIPHERAL MUSCLE-
BRAIN AXIS BIOMARKERS IN YOUNG
UNIVERSITY STUDENTS: A RANDOMIZED
PILOT TRIAL
SAFETY, LEARNING CURVE, IN ROBOTIC COLORECTAL
SURGERY: INITIAL EXPERIENCE FROM A TERTIARY
CENTER
M.C. Pedro Antonio Valdez Lizárraga
Autonomous University of Sinaloa
M.C. Perla Jacqueline Wlin Rodríguez
Autonomous University of Sinaloa
Dr. Víctor Manuel Martínez García
Instituto Tecnológico de Querétaro, México
Dra. Yennifer Díaz Romero
Universidad del Ejército, Fuerza Aérea y Guardia Nacional.
M.C. Gloria Patricia Garcia Lopez
Benemérita Universidad Autónoma de Puebla
pág. 4544
DOI: https://doi.org/10.37811/cl_rcm.v10i3.24499
Effects of Linear and Undulating Resistance Training Periodization on
Executive Functions, Physical Adaptations, and Peripheral Muscle-Brain
Axis Biomarkers in Young University Students: A Randomized Pilot Trial
M.C. Pedro Antonio Valdez Lizárraga1
Pedro.valdez@uas.edu.mx
https://orcid.org/0000-0001-5773-4628
Autonomous University of Sinaloa
M.C. Perla Jacqueline Wlin Rodríguez
perlajacqueline.rodriguez@uas.edu.mx
https://orcid.org/0009-0002-9343-4870
Autonomous University of Sinaloa
Dr. Víctor Manuel Martínez García
urs.dgip@uas.edu.mx
https://orcid.org/0009-0008-2647-9386
Autonomous University of Sinaloa
M.C. Gloria Patricia Garcia Lopez
gopagalo@hotmail.com
https://orcid.org/0009-0009-6338-4674
Dra. Yennifer Díaz Romero
urs.dgip@uas.edu.mx
https://orcid.org/0009-0009-7232-9749
Autonomous University of Sinaloa
Autonomous University of Sinaloa
ABSTRACT
The potential contribution of resistance training to cognitive and systemic health has received increasing
attention; however, less is known about whether different periodization models can be feasibly
implemented in university settings while producing preliminary signals in executive functions, physical
adaptations, and peripheral biomarkers related to the muscle-brain axis. This pilot randomized
controlled trial examined the feasibility, safety, acceptability, and preliminary effects of 12 weeks of
linear and undulating resistance training periodization compared with an active control condition in
young university students. Sixty participants were randomized in a 1:1:1 ratio to linear periodization,
undulating periodization, or active control. The primary outcome was feasibility, assessed through
retention, adherence, data completeness, fidelity, acceptability, and adverse events. Secondary outcomes
included inhibitory control, working memory, cognitive flexibility, estimated maximal strength,
handgrip strength, countermovement jump, muscle mass, and body fat. Exploratory outcomes included
peripheral BDNF, cathepsin B, IGF-1, IL-6, and C-reactive protein. Analyses included descriptive
statistics, linear mixed models, ANCOVA sensitivity models, complete-case and per-protocol
comparisons, Hedges’ g, and exploratory association analyses. Posttest retention was 95.0%, data
completeness was 95.0%, per-protocol inclusion was 90.0%, and no serious adverse events were
observed. Adherence was high across groups, and acceptability was favorable, although lower in the
active control group. Significant group-by-time signals were observed for executive function outcomes,
physical performance, body composition, and peripheral biomarkers, with larger preliminary changes
in the resistance training groups than in the active control condition. The findings support the feasibility
and preliminary analytical stability of a university-based periodized resistance training protocol.
Nevertheless, biomarker findings should be interpreted as peripheral exploration signals rather than
direct evidence of central neuroplasticity. A fully powered preregistered trial is warranted to confirm
efficacy and clarify mechanisms.
Keywords: Resistance training; periodization; executive functions; muscle-brain axis; BDNF; cathepsin
B; pilot randomized trial; university students.
1 Autor principal
Correspondencia: Pedro.valdez@uas.edu.mx
DOI: https://doi.org/10.37811/cl_rcm.v10i3.24499
Effects of Linear and Undulating Resistance Training Periodization on
Executive Functions, Physical Adaptations, and Peripheral Muscle-Brain
Axis Biomarkers in Young University Students: A Randomized Pilot Trial
M.C. Pedro Antonio Valdez Lizárraga1
Pedro.valdez@uas.edu.mx
https://orcid.org/0000-0001-5773-4628
Autonomous University of Sinaloa
M.C. Perla Jacqueline Wlin Rodríguez
perlajacqueline.rodriguez@uas.edu.mx
https://orcid.org/0009-0002-9343-4870
Autonomous University of Sinaloa
Dr. Víctor Manuel Martínez García
urs.dgip@uas.edu.mx
https://orcid.org/0009-0008-2647-9386
Autonomous University of Sinaloa
M.C. Gloria Patricia Garcia Lopez
gopagalo@hotmail.com
https://orcid.org/0009-0009-6338-4674
Dra. Yennifer Díaz Romero
urs.dgip@uas.edu.mx
https://orcid.org/0009-0009-7232-9749
Autonomous University of Sinaloa
Autonomous University of Sinaloa
ABSTRACT
The potential contribution of resistance training to cognitive and systemic health has received increasing
attention; however, less is known about whether different periodization models can be feasibly
implemented in university settings while producing preliminary signals in executive functions, physical
adaptations, and peripheral biomarkers related to the muscle-brain axis. This pilot randomized
controlled trial examined the feasibility, safety, acceptability, and preliminary effects of 12 weeks of
linear and undulating resistance training periodization compared with an active control condition in
young university students. Sixty participants were randomized in a 1:1:1 ratio to linear periodization,
undulating periodization, or active control. The primary outcome was feasibility, assessed through
retention, adherence, data completeness, fidelity, acceptability, and adverse events. Secondary outcomes
included inhibitory control, working memory, cognitive flexibility, estimated maximal strength,
handgrip strength, countermovement jump, muscle mass, and body fat. Exploratory outcomes included
peripheral BDNF, cathepsin B, IGF-1, IL-6, and C-reactive protein. Analyses included descriptive
statistics, linear mixed models, ANCOVA sensitivity models, complete-case and per-protocol
comparisons, Hedges’ g, and exploratory association analyses. Posttest retention was 95.0%, data
completeness was 95.0%, per-protocol inclusion was 90.0%, and no serious adverse events were
observed. Adherence was high across groups, and acceptability was favorable, although lower in the
active control group. Significant group-by-time signals were observed for executive function outcomes,
physical performance, body composition, and peripheral biomarkers, with larger preliminary changes
in the resistance training groups than in the active control condition. The findings support the feasibility
and preliminary analytical stability of a university-based periodized resistance training protocol.
Nevertheless, biomarker findings should be interpreted as peripheral exploration signals rather than
direct evidence of central neuroplasticity. A fully powered preregistered trial is warranted to confirm
efficacy and clarify mechanisms.
Keywords: Resistance training; periodization; executive functions; muscle-brain axis; BDNF; cathepsin
B; pilot randomized trial; university students.
1 Autor principal
Correspondencia: Pedro.valdez@uas.edu.mx
pág. 4545
Efectos de la periodización lineal y ondulatoria del entrenamiento de
resistencia sobre las funciones ejecutivas, las adaptaciones físicas y los
biomarcadores del eje músculo-cerebral periférico en jóvenes
universitarios: un ensayo piloto aleatorizado
RESUMEN
La posible contribución del entrenamiento de fuerza a la salud cognitiva y sistémica ha recibido una
atención creciente; sin embargo, se conoce menos sobre si diferentes modelos de periodización pueden
implementarse de manera factible en entornos universitarios y, al mismo tiempo, producir señales
preliminares en las funciones ejecutivas, las adaptaciones físicas y los biomarcadores periféricos
relacionados con el eje músculo-cerebro. Este ensayo piloto aleatorizado y controlado examinó la
factibilidad, seguridad, aceptabilidad y efectos preliminares de 12 semanas de periodización lineal y
ondulante del entrenamiento de fuerza, en comparación con una condición de control activo, en
estudiantes universitarios jóvenes. Sesenta participantes fueron aleatorizados en una proporción 1:1:1 a
periodización lineal, periodización ondulante o control activo. El desenlace primario fue la factibilidad,
evaluada mediante retención, adherencia, completitud de datos, fidelidad, aceptabilidad y eventos
adversos. Los desenlaces secundarios incluyeron control inhibitorio, memoria de trabajo, flexibilidad
cognitiva, fuerza máxima estimada, fuerza prensil, salto con contramovimiento, masa muscular y grasa
corporal. Los desenlaces exploratorios incluyeron BDNF periférico, catepsina B, IGF-1, IL-6 y proteína
C reactiva. Los análisis incluyeron estadística descriptiva, modelos lineales mixtos, modelos de
sensibilidad mediante ANCOVA, comparaciones de casos completos y por protocolo, g de Hedges y
análisis exploratorios de asociación. La retención postest fue de 95.0 %, la completitud de datos fue de
95.0 %, la inclusión por protocolo fue de 90.0 % y no se observaron eventos adversos graves. La
adherencia fue alta en todos los grupos y la aceptabilidad fue favorable, aunque menor en el grupo de
control activo. Se observaron señales significativas de interacción grupo por tiempo en los desenlaces
de función ejecutiva, rendimiento físico, composición corporal y biomarcadores periféricos, con
cambios preliminares mayores en los grupos de entrenamiento de fuerza que en la condición de control
activo. Los hallazgos respaldan la factibilidad y la estabilidad analítica preliminar de un protocolo
universitario de entrenamiento de fuerza periodizado. No obstante, los hallazgos relacionados con
biomarcadores deben interpretarse como señales exploratorias periféricas y no como evidencia directa
de neuroplasticidad central. Se justifica realizar un ensayo preregistrado con potencia estadística
suficiente para confirmar la eficacia y clarificar los mecanismos.
Palabras clave: entrenamiento de fuerza; periodización; funciones ejecutivas; eje músculo-cerebro;
BDNF; catepsina B; ensayo piloto aleatorizado; estudiantes universitarios.
Artículo recibido 25 abril 2026
Aceptado para publicación: 25 mayo 2026
Efectos de la periodización lineal y ondulatoria del entrenamiento de
resistencia sobre las funciones ejecutivas, las adaptaciones físicas y los
biomarcadores del eje músculo-cerebral periférico en jóvenes
universitarios: un ensayo piloto aleatorizado
RESUMEN
La posible contribución del entrenamiento de fuerza a la salud cognitiva y sistémica ha recibido una
atención creciente; sin embargo, se conoce menos sobre si diferentes modelos de periodización pueden
implementarse de manera factible en entornos universitarios y, al mismo tiempo, producir señales
preliminares en las funciones ejecutivas, las adaptaciones físicas y los biomarcadores periféricos
relacionados con el eje músculo-cerebro. Este ensayo piloto aleatorizado y controlado examinó la
factibilidad, seguridad, aceptabilidad y efectos preliminares de 12 semanas de periodización lineal y
ondulante del entrenamiento de fuerza, en comparación con una condición de control activo, en
estudiantes universitarios jóvenes. Sesenta participantes fueron aleatorizados en una proporción 1:1:1 a
periodización lineal, periodización ondulante o control activo. El desenlace primario fue la factibilidad,
evaluada mediante retención, adherencia, completitud de datos, fidelidad, aceptabilidad y eventos
adversos. Los desenlaces secundarios incluyeron control inhibitorio, memoria de trabajo, flexibilidad
cognitiva, fuerza máxima estimada, fuerza prensil, salto con contramovimiento, masa muscular y grasa
corporal. Los desenlaces exploratorios incluyeron BDNF periférico, catepsina B, IGF-1, IL-6 y proteína
C reactiva. Los análisis incluyeron estadística descriptiva, modelos lineales mixtos, modelos de
sensibilidad mediante ANCOVA, comparaciones de casos completos y por protocolo, g de Hedges y
análisis exploratorios de asociación. La retención postest fue de 95.0 %, la completitud de datos fue de
95.0 %, la inclusión por protocolo fue de 90.0 % y no se observaron eventos adversos graves. La
adherencia fue alta en todos los grupos y la aceptabilidad fue favorable, aunque menor en el grupo de
control activo. Se observaron señales significativas de interacción grupo por tiempo en los desenlaces
de función ejecutiva, rendimiento físico, composición corporal y biomarcadores periféricos, con
cambios preliminares mayores en los grupos de entrenamiento de fuerza que en la condición de control
activo. Los hallazgos respaldan la factibilidad y la estabilidad analítica preliminar de un protocolo
universitario de entrenamiento de fuerza periodizado. No obstante, los hallazgos relacionados con
biomarcadores deben interpretarse como señales exploratorias periféricas y no como evidencia directa
de neuroplasticidad central. Se justifica realizar un ensayo preregistrado con potencia estadística
suficiente para confirmar la eficacia y clarificar los mecanismos.
Palabras clave: entrenamiento de fuerza; periodización; funciones ejecutivas; eje músculo-cerebro;
BDNF; catepsina B; ensayo piloto aleatorizado; estudiantes universitarios.
Artículo recibido 25 abril 2026
Aceptado para publicación: 25 mayo 2026
pág. 4546
INTRODUCTION
Resistance training has traditionally been framed as a method for improving muscular strength,
hypertrophy, neuromuscular performance, body composition, and functional capacity. In contemporary
exercise science, however, this view has expanded toward a systemic interpretation of skeletal muscle
as an adaptive tissue with mechanical, metabolic, endocrine, and immunoregulatory roles. This broader
perspective is relevant for university populations because young adulthood is a period in which physical
inactivity, academic stress, sleep disruption, and high cognitive demand may converge. In this context,
resistance training is not only a physical conditioning strategy, but also a plausible intervention for
studying interactions between muscular adaptation, executive functioning, and peripheral biological
signals associated with exercise-induced systemic regulation.
Recent evidence supports the general premise that exercise can benefit cognition, memory, and
executive function across populations, although the magnitude of effect varies according to age, health
status, exercise modality, intervention duration, intensity, and cognitive domain. In an umbrella review
and meta-meta-analysis of randomized controlled trial evidence, Singh et al. (2025) reported favorable
effects of exercise on general cognition, memory, and executive function, reinforcing the relevance of
physical exercise as a broad strategy for cognitive health. Nevertheless, this evidence does not resolve
which specific training structures are most feasible or potentially effective in young university students,
nor does it clarify whether organizing resistance training through different periodization models
produces distinct cognitive, physical, or peripheral biomarker responses. Therefore, a more specific
experimental approach is warranted.
Resistance training may be particularly relevant for executive functions because it combines force
production, motor planning, effort regulation, attentional control, interoceptive monitoring, and
progressive adaptation to increasing task demands. Executive functions are commonly conceptualized
around core domains such as inhibitory control, working memory, and cognitive flexibility, which
support goal-directed behavior, academic performance, self-regulation, and adaptive decision-making
(Diamond, 2013; Miyake et al., 2000). In university settings, these domains are not merely laboratory
constructs; they are functionally related to study behavior, sustained attention, emotional regulation, and
the ability to adapt to changing academic demands. From this perspective, examining whether structured
INTRODUCTION
Resistance training has traditionally been framed as a method for improving muscular strength,
hypertrophy, neuromuscular performance, body composition, and functional capacity. In contemporary
exercise science, however, this view has expanded toward a systemic interpretation of skeletal muscle
as an adaptive tissue with mechanical, metabolic, endocrine, and immunoregulatory roles. This broader
perspective is relevant for university populations because young adulthood is a period in which physical
inactivity, academic stress, sleep disruption, and high cognitive demand may converge. In this context,
resistance training is not only a physical conditioning strategy, but also a plausible intervention for
studying interactions between muscular adaptation, executive functioning, and peripheral biological
signals associated with exercise-induced systemic regulation.
Recent evidence supports the general premise that exercise can benefit cognition, memory, and
executive function across populations, although the magnitude of effect varies according to age, health
status, exercise modality, intervention duration, intensity, and cognitive domain. In an umbrella review
and meta-meta-analysis of randomized controlled trial evidence, Singh et al. (2025) reported favorable
effects of exercise on general cognition, memory, and executive function, reinforcing the relevance of
physical exercise as a broad strategy for cognitive health. Nevertheless, this evidence does not resolve
which specific training structures are most feasible or potentially effective in young university students,
nor does it clarify whether organizing resistance training through different periodization models
produces distinct cognitive, physical, or peripheral biomarker responses. Therefore, a more specific
experimental approach is warranted.
Resistance training may be particularly relevant for executive functions because it combines force
production, motor planning, effort regulation, attentional control, interoceptive monitoring, and
progressive adaptation to increasing task demands. Executive functions are commonly conceptualized
around core domains such as inhibitory control, working memory, and cognitive flexibility, which
support goal-directed behavior, academic performance, self-regulation, and adaptive decision-making
(Diamond, 2013; Miyake et al., 2000). In university settings, these domains are not merely laboratory
constructs; they are functionally related to study behavior, sustained attention, emotional regulation, and
the ability to adapt to changing academic demands. From this perspective, examining whether structured
pág. 4547
resistance training is associated with changes in Stroop performance, N-back accuracy, and Trail
Making Test B performance is theoretically justified and educationally relevant.
The available literature on resistance exercise and executive function suggests promise, but also
heterogeneity. Huang et al. (2022) found that acute resistance exercise can benefit executive function,
with effects moderated by intensity and by the executive domain assessed. Their review indicated that
inhibitory control, working memory, and cognitive flexibility may respond differently to resistance
exercise, and that moderate-intensity protocols appear especially relevant for some domains. However,
acute effects cannot be assumed to represent chronic adaptations, and findings from single exercise bouts
cannot be directly generalized to 12-week periodized programs. This distinction is important because
chronic resistance training introduces progressive overload, neuromuscular learning, recovery patterns,
adherence demands, and repeated exposure to structured effort, all of which may shape cognitive and
physiological outcomes differently from acute exercise.
Periodization is a central principle in resistance training prescription because it organizes training
variables across time to manage adaptation, fatigue, recovery, and progression. Linear periodization
usually progresses from higher volume and lower intensity toward lower volume and higher intensity
across successive phases. Undulating periodization varies volume and intensity more frequently, often
within the week, exposing participants to alternating stimuli such as hypertrophy-oriented, strength-
oriented, and power-oriented sessions. Existing comparative evidence does not support a simplistic
assumption that one model is universally superior. Earlier meta-analytic work suggested that differences
between linear and undulating periodization for strength or hypertrophy are often small or inconsistent
when training variables are reasonably controlled (Grgic et al., 2017; Harries et al., 2015). More recent
synthesis comparing linear and undulating periodization across athletic capacities and health-related
indicators also suggests that responses may depend on outcome, population, program duration, training
history, and dose equivalence (Zhang et al., 2026). Consequently, the present study does not frame
undulating or linear periodization as inherently superior. Instead, it treats periodization model as a
structured experimental contrast in how training load is organized over time.
This distinction is methodologically important. If the objective is to compare periodization models, both
resistance training arms must be similar in frequency, duration, exercise selection, supervision, and
resistance training is associated with changes in Stroop performance, N-back accuracy, and Trail
Making Test B performance is theoretically justified and educationally relevant.
The available literature on resistance exercise and executive function suggests promise, but also
heterogeneity. Huang et al. (2022) found that acute resistance exercise can benefit executive function,
with effects moderated by intensity and by the executive domain assessed. Their review indicated that
inhibitory control, working memory, and cognitive flexibility may respond differently to resistance
exercise, and that moderate-intensity protocols appear especially relevant for some domains. However,
acute effects cannot be assumed to represent chronic adaptations, and findings from single exercise bouts
cannot be directly generalized to 12-week periodized programs. This distinction is important because
chronic resistance training introduces progressive overload, neuromuscular learning, recovery patterns,
adherence demands, and repeated exposure to structured effort, all of which may shape cognitive and
physiological outcomes differently from acute exercise.
Periodization is a central principle in resistance training prescription because it organizes training
variables across time to manage adaptation, fatigue, recovery, and progression. Linear periodization
usually progresses from higher volume and lower intensity toward lower volume and higher intensity
across successive phases. Undulating periodization varies volume and intensity more frequently, often
within the week, exposing participants to alternating stimuli such as hypertrophy-oriented, strength-
oriented, and power-oriented sessions. Existing comparative evidence does not support a simplistic
assumption that one model is universally superior. Earlier meta-analytic work suggested that differences
between linear and undulating periodization for strength or hypertrophy are often small or inconsistent
when training variables are reasonably controlled (Grgic et al., 2017; Harries et al., 2015). More recent
synthesis comparing linear and undulating periodization across athletic capacities and health-related
indicators also suggests that responses may depend on outcome, population, program duration, training
history, and dose equivalence (Zhang et al., 2026). Consequently, the present study does not frame
undulating or linear periodization as inherently superior. Instead, it treats periodization model as a
structured experimental contrast in how training load is organized over time.
This distinction is methodologically important. If the objective is to compare periodization models, both
resistance training arms must be similar in frequency, duration, exercise selection, supervision, and
pág. 4548
general exposure, while differing primarily in the temporal distribution of intensity and volume.
Otherwise, any observed difference could reflect unequal dose rather than periodization structure. In a
pilot trial, this issue is especially relevant because feasibility outcomes, such as adherence, fidelity,
perceived exertion, acceptability, and safety, may determine whether the intervention can be
implemented with sufficient quality before attempting definitive efficacy claims. Therefore, a design
that monitors internal load, attendance, progression, and adverse events is necessary to interpret
cognitive, physical, and biomarker outcomes responsibly.
The biological rationale for examining peripheral biomarkers derives from the concept of skeletal
muscle as an endocrine organ. Contracting muscle can release myokines and other exercise-responsive
factors that participate in muscle-organ crosstalk, including communication with adipose tissue, liver,
bone, vasculature, immune pathways, and the brain (Severinsen & Pedersen, 2020). Within this
framework, the muscle-brain axis provides a plausible conceptual model for investigating how exercise-
related muscular adaptations may coincide with changes in peripheral neurotrophic, metabolic, or
inflammatory markers. However, this framework requires caution. Peripheral biomarkers are not direct
windows into the brain, and changes in blood-based markers should not be interpreted as proof of central
neuroplasticity, neurogenesis, or cognitive causation unless supported by stronger mechanistic methods.
Among candidate biomarkers, brain-derived neurotrophic factors have received substantial attention
because of their relevance to neuronal survival, synaptic plasticity, learning, and memory. Nevertheless,
BDNF measured in blood is methodologically complex. Serum and plasma values may be influenced
by matrix selection, platelet contribution, sample handling, storage, assay sensitivity, and preanalytical
variability. Want et al. (2023) emphasized that serum BDNF measurements can be strongly influenced
by platelet-derived BDNF, making functional interpretation of circulating levels difficult. Thus, in this
trial, BDNF is best described as a peripheral neurotrophic marker rather than as a direct indicator of
central neuroplasticity. This distinction is not merely semantic; it protects the study from
overinterpreting biomarker changes that may reflect systemic, hematological, or procedural factors.
Cathepsin B is another relevant exploratory marker because it has been proposed as an exercise-
responsive factor linking skeletal muscle, systemic circulation, and memory-related processes. Moon et
al. (2016) reported that exercise increased circulating cathepsin B in animal models, primates, and
general exposure, while differing primarily in the temporal distribution of intensity and volume.
Otherwise, any observed difference could reflect unequal dose rather than periodization structure. In a
pilot trial, this issue is especially relevant because feasibility outcomes, such as adherence, fidelity,
perceived exertion, acceptability, and safety, may determine whether the intervention can be
implemented with sufficient quality before attempting definitive efficacy claims. Therefore, a design
that monitors internal load, attendance, progression, and adverse events is necessary to interpret
cognitive, physical, and biomarker outcomes responsibly.
The biological rationale for examining peripheral biomarkers derives from the concept of skeletal
muscle as an endocrine organ. Contracting muscle can release myokines and other exercise-responsive
factors that participate in muscle-organ crosstalk, including communication with adipose tissue, liver,
bone, vasculature, immune pathways, and the brain (Severinsen & Pedersen, 2020). Within this
framework, the muscle-brain axis provides a plausible conceptual model for investigating how exercise-
related muscular adaptations may coincide with changes in peripheral neurotrophic, metabolic, or
inflammatory markers. However, this framework requires caution. Peripheral biomarkers are not direct
windows into the brain, and changes in blood-based markers should not be interpreted as proof of central
neuroplasticity, neurogenesis, or cognitive causation unless supported by stronger mechanistic methods.
Among candidate biomarkers, brain-derived neurotrophic factors have received substantial attention
because of their relevance to neuronal survival, synaptic plasticity, learning, and memory. Nevertheless,
BDNF measured in blood is methodologically complex. Serum and plasma values may be influenced
by matrix selection, platelet contribution, sample handling, storage, assay sensitivity, and preanalytical
variability. Want et al. (2023) emphasized that serum BDNF measurements can be strongly influenced
by platelet-derived BDNF, making functional interpretation of circulating levels difficult. Thus, in this
trial, BDNF is best described as a peripheral neurotrophic marker rather than as a direct indicator of
central neuroplasticity. This distinction is not merely semantic; it protects the study from
overinterpreting biomarker changes that may reflect systemic, hematological, or procedural factors.
Cathepsin B is another relevant exploratory marker because it has been proposed as an exercise-
responsive factor linking skeletal muscle, systemic circulation, and memory-related processes. Moon et
al. (2016) reported that exercise increased circulating cathepsin B in animal models, primates, and
pág. 4549
humans, and that circulating cathepsin B was associated with fitness and memory-related outcomes in
humans. These findings support the plausibility of including cathepsin B in an exploratory muscle-brain
axis panel. Nevertheless, the translation of this evidence to young university students undergoing
resistance training remains uncertain, particularly because much of the mechanistic literature is based
on endurance exercise, animal models, or older populations. Therefore, Cathepsin B should be
interpreted as hypothesis-generating rather than confirmatory.
IGF-1, IL-6, and C-reactive protein provide complementary systemic information. IGF-1 is relevant to
anabolic signaling, muscle adaptation, and neurotrophic pathways, but is also sensitive to nutrition,
sleep, developmental status, and metabolic context. IL-6 is particularly complex because it may reflect
inflammatory processes, muscle-derived signaling, or acute exercise responses depending on timing and
physiological context. C-reactive protein offers a broader index of low-grade systemic inflammation,
although it is nonspecific and can be affected by infection, stress, adiposity, sleep, and recent physical
exertion. For these reasons, the biomarker panel in this study should be positioned as exploratory and
peripheral. Its purpose is to examine whether favorable physical and executive function changes co-
occur with systemic signals compatible with a muscle-brain axis framework, not to demonstrate a causal
molecular pathway.
METHODOLOGY
Study Design
This study was structured as a three-arm, parallel-group, randomized pilot-controlled trial with blinded
outcome assessment. Participants were allocated in a 1:1:1 ratio to one of three conditions: linear
resistance training periodization, undulating resistance training periodization, or active control. The
intervention lasted 12 weeks and included three supervised sessions per week. Assessments were
organized at baseline, midpoint monitoring, and posttest, with feasibility defined as the primary
outcome.
The methodological rationale followed the Standard Protocol Items: Recommendations for
Interventional Trials (SPIRIT) statement, which establishes that a clinical trial protocol should function
as the foundation for study planning, conduct, reporting, and appraisal (Chan et al., 2013). Because this
was a pilot trial, reporting and interpretation were additionally aligned with the CONSORT extension
humans, and that circulating cathepsin B was associated with fitness and memory-related outcomes in
humans. These findings support the plausibility of including cathepsin B in an exploratory muscle-brain
axis panel. Nevertheless, the translation of this evidence to young university students undergoing
resistance training remains uncertain, particularly because much of the mechanistic literature is based
on endurance exercise, animal models, or older populations. Therefore, Cathepsin B should be
interpreted as hypothesis-generating rather than confirmatory.
IGF-1, IL-6, and C-reactive protein provide complementary systemic information. IGF-1 is relevant to
anabolic signaling, muscle adaptation, and neurotrophic pathways, but is also sensitive to nutrition,
sleep, developmental status, and metabolic context. IL-6 is particularly complex because it may reflect
inflammatory processes, muscle-derived signaling, or acute exercise responses depending on timing and
physiological context. C-reactive protein offers a broader index of low-grade systemic inflammation,
although it is nonspecific and can be affected by infection, stress, adiposity, sleep, and recent physical
exertion. For these reasons, the biomarker panel in this study should be positioned as exploratory and
peripheral. Its purpose is to examine whether favorable physical and executive function changes co-
occur with systemic signals compatible with a muscle-brain axis framework, not to demonstrate a causal
molecular pathway.
METHODOLOGY
Study Design
This study was structured as a three-arm, parallel-group, randomized pilot-controlled trial with blinded
outcome assessment. Participants were allocated in a 1:1:1 ratio to one of three conditions: linear
resistance training periodization, undulating resistance training periodization, or active control. The
intervention lasted 12 weeks and included three supervised sessions per week. Assessments were
organized at baseline, midpoint monitoring, and posttest, with feasibility defined as the primary
outcome.
The methodological rationale followed the Standard Protocol Items: Recommendations for
Interventional Trials (SPIRIT) statement, which establishes that a clinical trial protocol should function
as the foundation for study planning, conduct, reporting, and appraisal (Chan et al., 2013). Because this
was a pilot trial, reporting and interpretation were additionally aligned with the CONSORT extension
pág. 4550
for randomized pilot and feasibility trials. This extension emphasizes that randomized pilot trials
conducted before a definitive trial should primarily reduce uncertainty regarding feasibility, recruitment,
retention, adherence, safety, acceptability, measurement procedures, and progression criteria, rather than
make definitive claims of efficacy (Eldridge et al., 2016). Consequently, the present study prioritized
feasibility and analytical stability over confirmatory inference.
Context and Participants
The study was conducted in a university-based exercise science context, using institutional spaces
suitable for physical assessment, supervised resistance training, active control sessions, and cognitive
testing. The target population consisted of young university students aged 18 to 25 years. This
population was selected because young adulthood is characterized by high academic demands, executive
function requirements, variable sleep patterns, and modifiable physical activity behaviors. In addition,
university students represent a feasible population for structured exercise interventions under supervised
academic conditions.
A total of 60 participants were randomized, with 20 assigned to each study arm. The sample size was
consistent with the logic of a pilot randomized trial, whose main purpose is to estimate feasibility
indicators, variability, adherence, retention, and preliminary effect sizes for a future definitive trial. The
sample was not intended to provide a definitive test of efficacy or mechanism.
Eligibility Criteria
Participants were eligible if they met the following inclusion criteria: being between 18 and 25 years of
age, being an active university student, providing written informed consent, being apparently healthy or
cleared for participation in moderate to vigorous exercise, having no systematic resistance training
experience during the previous six months, and being available to attend three supervised sessions per
week for 12 weeks.
Exclusion criteria included any medical condition contraindicating exercise participation, recent
musculoskeletal injury limiting resistance training or physical testing, neurological or cardiovascular
conditions requiring clinical restriction, current participation in another structured resistance training
program, use of non-prescribed anabolic agents or hormonal ergogenic substances, pregnancy, or
inability to complete baseline assessments. Participants were also excluded if they presented any safety
for randomized pilot and feasibility trials. This extension emphasizes that randomized pilot trials
conducted before a definitive trial should primarily reduce uncertainty regarding feasibility, recruitment,
retention, adherence, safety, acceptability, measurement procedures, and progression criteria, rather than
make definitive claims of efficacy (Eldridge et al., 2016). Consequently, the present study prioritized
feasibility and analytical stability over confirmatory inference.
Context and Participants
The study was conducted in a university-based exercise science context, using institutional spaces
suitable for physical assessment, supervised resistance training, active control sessions, and cognitive
testing. The target population consisted of young university students aged 18 to 25 years. This
population was selected because young adulthood is characterized by high academic demands, executive
function requirements, variable sleep patterns, and modifiable physical activity behaviors. In addition,
university students represent a feasible population for structured exercise interventions under supervised
academic conditions.
A total of 60 participants were randomized, with 20 assigned to each study arm. The sample size was
consistent with the logic of a pilot randomized trial, whose main purpose is to estimate feasibility
indicators, variability, adherence, retention, and preliminary effect sizes for a future definitive trial. The
sample was not intended to provide a definitive test of efficacy or mechanism.
Eligibility Criteria
Participants were eligible if they met the following inclusion criteria: being between 18 and 25 years of
age, being an active university student, providing written informed consent, being apparently healthy or
cleared for participation in moderate to vigorous exercise, having no systematic resistance training
experience during the previous six months, and being available to attend three supervised sessions per
week for 12 weeks.
Exclusion criteria included any medical condition contraindicating exercise participation, recent
musculoskeletal injury limiting resistance training or physical testing, neurological or cardiovascular
conditions requiring clinical restriction, current participation in another structured resistance training
program, use of non-prescribed anabolic agents or hormonal ergogenic substances, pregnancy, or
inability to complete baseline assessments. Participants were also excluded if they presented any safety
pág. 4551
condition identified during screening that made resistance training participation inappropriate without
medical evaluation.
Randomization and Blinding
After baseline assessment, participants were randomized in a 1:1:1 ratio to linear periodization,
undulating periodization, or active control. The randomization sequence was generated using a
computer-based procedure. Allocation was concealed until baseline measurements were completed.
Assignment was communicated only after eligibility confirmation, informed consent, and baseline
testing.
Because of the nature of the exercise intervention, participants and trainers could not be blinded to group
allocation. Nevertheless, outcome assessors were blinded whenever feasible. Cognitive and physical
evaluators were instructed not to ask about group allocation, and participants were asked not to disclose
their assigned condition during assessments. If laboratory analyses were conducted, biological samples
were coded so that the laboratory personnel were unaware of group allocation. When feasible, the
statistical dataset was coded using group labels that masked the intervention condition during initial
analysis.
Interventions
The intervention description was aligned with the Template for Intervention Description and Replication
(TIDieR) checklist and the Consensus on Exercise Reporting Template (CERT). TIDieR was developed
to improve the completeness and replicability of intervention descriptions by specifying what was
delivered, by whom, how much, and with what modifications (Hoffmann et al., 2014). CERT was
specifically developed to improve the reporting of exercise interventions, including dose, tailoring,
progression, supervision, adherence, and fidelity (Slade et al., 2016). These frameworks were used
because incomplete reporting of exercise protocols limits replication, implementation, and
interpretation.
All intervention arms included three supervised sessions per week for 12 weeks. The two resistance
training groups used the same general session structure, exercise patterns, supervision procedures, and
safety monitoring. Each session included brief pre-session screening, general warm-up, specific warm-
up, main training block, complementary exercises, cool-down, and session rating of perceived exertion
condition identified during screening that made resistance training participation inappropriate without
medical evaluation.
Randomization and Blinding
After baseline assessment, participants were randomized in a 1:1:1 ratio to linear periodization,
undulating periodization, or active control. The randomization sequence was generated using a
computer-based procedure. Allocation was concealed until baseline measurements were completed.
Assignment was communicated only after eligibility confirmation, informed consent, and baseline
testing.
Because of the nature of the exercise intervention, participants and trainers could not be blinded to group
allocation. Nevertheless, outcome assessors were blinded whenever feasible. Cognitive and physical
evaluators were instructed not to ask about group allocation, and participants were asked not to disclose
their assigned condition during assessments. If laboratory analyses were conducted, biological samples
were coded so that the laboratory personnel were unaware of group allocation. When feasible, the
statistical dataset was coded using group labels that masked the intervention condition during initial
analysis.
Interventions
The intervention description was aligned with the Template for Intervention Description and Replication
(TIDieR) checklist and the Consensus on Exercise Reporting Template (CERT). TIDieR was developed
to improve the completeness and replicability of intervention descriptions by specifying what was
delivered, by whom, how much, and with what modifications (Hoffmann et al., 2014). CERT was
specifically developed to improve the reporting of exercise interventions, including dose, tailoring,
progression, supervision, adherence, and fidelity (Slade et al., 2016). These frameworks were used
because incomplete reporting of exercise protocols limits replication, implementation, and
interpretation.
All intervention arms included three supervised sessions per week for 12 weeks. The two resistance
training groups used the same general session structure, exercise patterns, supervision procedures, and
safety monitoring. Each session included brief pre-session screening, general warm-up, specific warm-
up, main training block, complementary exercises, cool-down, and session rating of perceived exertion
pág. 4552
(RPE). The main movement patterns included knee-dominant, hip-dominant, horizontal push, horizontal
pull, vertical push or pull, and core stabilization exercises. Loads were adjusted according to technical
execution, estimated strength level, RPE, and repetitions in reserve. Participants were not systematically
trained to muscular failure.
Linear Periodization Group
Participants assigned to linear periodization completed a progressive 12-week resistance training
program in which volume and intensity were organized sequentially across the intervention. The initial
weeks emphasized anatomical adaptation, movement technique, and tolerance to resistance exercise.
Subsequent weeks progressively increased training demand through hypertrophy-oriented loading,
submaximal strength work, controlled power-oriented exercises, and a relative deload or consolidation
phase before posttest assessment.
The defining feature of the linear model was gradual progression across phases. Training intensity
increased in a structured manner, while total volume was adjusted to manage fatigue and support
adaptation. This approach provided a conventional progression from technical preparation to higher
neuromuscular demand.
Undulating Periodization Group
Participants assigned to undulating periodization completed a 12-week resistance training program using
the same general exercises and session frequency as the linear group, but with more frequent variation
in training stimulus. Weekly micro cycles alternate sessions emphasizing hypertrophy-oriented work,
submaximal strength work, and controlled power or force-velocity work. The purpose was to vary
intensity, repetitions, and neuromuscular demand within the week while maintaining comparable
supervision and general exposure.
The defining feature of the undulating model was the temporal distribution of training load, not a higher
overall training dose. Therefore, the comparison between the linear and undulating groups was
interpreted as a comparison of load organization rather than as a comparison between training and non-
training or between low and high total dose.
Active Control Group
(RPE). The main movement patterns included knee-dominant, hip-dominant, horizontal push, horizontal
pull, vertical push or pull, and core stabilization exercises. Loads were adjusted according to technical
execution, estimated strength level, RPE, and repetitions in reserve. Participants were not systematically
trained to muscular failure.
Linear Periodization Group
Participants assigned to linear periodization completed a progressive 12-week resistance training
program in which volume and intensity were organized sequentially across the intervention. The initial
weeks emphasized anatomical adaptation, movement technique, and tolerance to resistance exercise.
Subsequent weeks progressively increased training demand through hypertrophy-oriented loading,
submaximal strength work, controlled power-oriented exercises, and a relative deload or consolidation
phase before posttest assessment.
The defining feature of the linear model was gradual progression across phases. Training intensity
increased in a structured manner, while total volume was adjusted to manage fatigue and support
adaptation. This approach provided a conventional progression from technical preparation to higher
neuromuscular demand.
Undulating Periodization Group
Participants assigned to undulating periodization completed a 12-week resistance training program using
the same general exercises and session frequency as the linear group, but with more frequent variation
in training stimulus. Weekly micro cycles alternate sessions emphasizing hypertrophy-oriented work,
submaximal strength work, and controlled power or force-velocity work. The purpose was to vary
intensity, repetitions, and neuromuscular demand within the week while maintaining comparable
supervision and general exposure.
The defining feature of the undulating model was the temporal distribution of training load, not a higher
overall training dose. Therefore, the comparison between the linear and undulating groups was
interpreted as a comparison of load organization rather than as a comparison between training and non-
training or between low and high total dose.
Active Control Group
pág. 4553
The active control group attended supervised sessions with the same general frequency and similar
contact time but without progressive resistance training. Sessions included mobility, stretching, body
awareness, low-intensity movement, breathing exercises, and health-related body education. The active
control condition was selected to reduce nonspecific effects related to attention, supervision, routine,
group interaction, and expectation. It was not designed to produce substantial resistance training
adaptations.
Active control participants did not complete progressive overload, strength-oriented sets near failure, or
structured resistance training designed to improve maximal strength, hypertrophy, or power.
Attendance, perceived exertion, safety events, and acceptability were monitored in the same manner as
in the resistance training groups.
Outcomes and Measures
Primary Outcome: Feasibility
The primary outcome was feasibility of the 12-week university-based protocol. Feasibility was
operationalized through retention, adherence, data completeness, intervention fidelity, acceptability, and
adverse events. Retention was calculated as the proportion of randomized participants who completed
posttest assessment. Adherence was calculated as the proportion of scheduled sessions attended. Data
completeness was calculated as the proportion of expected measurements successfully obtained. Fidelity
referred to the proportion of intervention components delivered according to protocol. Acceptability was
assessed using a brief postintervention questionnaire. Safety was assessed through systematic
registration of adverse events classified as mild, moderate, or serious.
The feasibility framework was prioritized because randomized pilot trials are designed to determine
whether the methods, intervention, and measurement procedures are suitable for a larger definitive study
(Eldridge et al., 2016). Therefore, feasibility indicators were interpreted before secondary and
exploratory outcomes.
Secondary Cognitive Outcomes
Executive function outcomes included inhibitory control, working memory, and cognitive flexibility.
Inhibitory control was assessed through Stroop performance, with lower response times or interference
scores interpreted as better performance when applicable. Working memory was assessed through N-
The active control group attended supervised sessions with the same general frequency and similar
contact time but without progressive resistance training. Sessions included mobility, stretching, body
awareness, low-intensity movement, breathing exercises, and health-related body education. The active
control condition was selected to reduce nonspecific effects related to attention, supervision, routine,
group interaction, and expectation. It was not designed to produce substantial resistance training
adaptations.
Active control participants did not complete progressive overload, strength-oriented sets near failure, or
structured resistance training designed to improve maximal strength, hypertrophy, or power.
Attendance, perceived exertion, safety events, and acceptability were monitored in the same manner as
in the resistance training groups.
Outcomes and Measures
Primary Outcome: Feasibility
The primary outcome was feasibility of the 12-week university-based protocol. Feasibility was
operationalized through retention, adherence, data completeness, intervention fidelity, acceptability, and
adverse events. Retention was calculated as the proportion of randomized participants who completed
posttest assessment. Adherence was calculated as the proportion of scheduled sessions attended. Data
completeness was calculated as the proportion of expected measurements successfully obtained. Fidelity
referred to the proportion of intervention components delivered according to protocol. Acceptability was
assessed using a brief postintervention questionnaire. Safety was assessed through systematic
registration of adverse events classified as mild, moderate, or serious.
The feasibility framework was prioritized because randomized pilot trials are designed to determine
whether the methods, intervention, and measurement procedures are suitable for a larger definitive study
(Eldridge et al., 2016). Therefore, feasibility indicators were interpreted before secondary and
exploratory outcomes.
Secondary Cognitive Outcomes
Executive function outcomes included inhibitory control, working memory, and cognitive flexibility.
Inhibitory control was assessed through Stroop performance, with lower response times or interference
scores interpreted as better performance when applicable. Working memory was assessed through N-
pág. 4554
back accuracy, with higher accuracy interpreted as better performance. Cognitive flexibility was
assessed through Trail Making Test B performance, with lower completion time interpreted as better
performance.
These three executive domains were selected because inhibitory control, working memory, and
cognitive flexibility represent core components of executive function and are relevant to academic
behavior, self-regulation, and adaptive performance in university students.
Secondary Physical and Morphological Outcomes
Physical outcomes included estimated one-repetition maximum (1RM), handgrip strength, and
countermovement jump performance. Estimated 1RM was used instead of direct maximal testing to
reduce risk and increase feasibility in a pilot sample that had not engaged in systematic resistance
training during the previous six months. Handgrip strength was assessed using dynamometry, and
countermovement jump performance was used as an indicator of lower-body neuromuscular
performance.
Morphological outcomes included muscle mass and body fat percentage. These were assessed using
standardized body composition procedures available in the institutional setting. Measurements were
conducted under controlled conditions, including similar timing and preassessment instructions
whenever possible.
Exploratory Peripheral Biomarkers
Exploratory biomarkers included brain-derived neurotrophic factors (BDNF), cathepsin B, insulin-like
growth factor 1 (IGF-1), interleukin 6 (IL-6), and C-reactive protein (CRP), when laboratory conditions
allowed. These markers were interpreted as peripheral exploratory indicators related to neurotrophic,
metabolic, and inflammatory pathways. They were not interpreted as direct evidence of central
neuroplasticity.
BDNF was treated as a peripheral neurotrophic marker because blood concentrations may be influenced
by matrix selection, platelet release, sample handling, and preanalytical variability. Cathepsin B was
included as an exploratory marker related to exercise-responsive systemic signaling. IGF-1, IL-6, and
CRP were included to provide complementary information on anabolic, immunometabolic, and
inflammatory status. Biomarker interpretation emphasized caution because peripheral circulating
back accuracy, with higher accuracy interpreted as better performance. Cognitive flexibility was
assessed through Trail Making Test B performance, with lower completion time interpreted as better
performance.
These three executive domains were selected because inhibitory control, working memory, and
cognitive flexibility represent core components of executive function and are relevant to academic
behavior, self-regulation, and adaptive performance in university students.
Secondary Physical and Morphological Outcomes
Physical outcomes included estimated one-repetition maximum (1RM), handgrip strength, and
countermovement jump performance. Estimated 1RM was used instead of direct maximal testing to
reduce risk and increase feasibility in a pilot sample that had not engaged in systematic resistance
training during the previous six months. Handgrip strength was assessed using dynamometry, and
countermovement jump performance was used as an indicator of lower-body neuromuscular
performance.
Morphological outcomes included muscle mass and body fat percentage. These were assessed using
standardized body composition procedures available in the institutional setting. Measurements were
conducted under controlled conditions, including similar timing and preassessment instructions
whenever possible.
Exploratory Peripheral Biomarkers
Exploratory biomarkers included brain-derived neurotrophic factors (BDNF), cathepsin B, insulin-like
growth factor 1 (IGF-1), interleukin 6 (IL-6), and C-reactive protein (CRP), when laboratory conditions
allowed. These markers were interpreted as peripheral exploratory indicators related to neurotrophic,
metabolic, and inflammatory pathways. They were not interpreted as direct evidence of central
neuroplasticity.
BDNF was treated as a peripheral neurotrophic marker because blood concentrations may be influenced
by matrix selection, platelet release, sample handling, and preanalytical variability. Cathepsin B was
included as an exploratory marker related to exercise-responsive systemic signaling. IGF-1, IL-6, and
CRP were included to provide complementary information on anabolic, immunometabolic, and
inflammatory status. Biomarker interpretation emphasized caution because peripheral circulating
pág. 4555
markers cannot establish direct brain-level mechanisms in the absence of neuroimaging, cerebrospinal
fluid measures, or more direct neurophysiological methods.
Covariates
Potential covariates included sleep quality, external physical activity, academic stress, caffeine intake,
screen exposure, alcohol use, dietary conditions before testing, menstrual cycle phase when applicable,
time of assessment, and baseline value of the outcome. These covariates were selected because they may
influence executive performance, recovery, perceived exertion, inflammatory status, and body
composition. Covariates were used descriptively and, when methodologically justified, in adjusted
sensitivity models.
Procedure
The study procedure consisted of familiarization, baseline assessment, randomization, 12-week
intervention, midpoint monitoring, posttest assessment, and optional follow-up if retained in the
protocol.
During familiarization, participants received general instructions, practiced cognitive and physical
testing procedures, and were oriented regarding safety, attendance, RPE reporting, and intervention
expectations. Familiarization was included to reduce learning effects, test anxiety, and procedural
variability.
Baseline assessment was conducted before randomization. It included eligibility confirmation,
preassessment condition verification, executive function testing, physical performance testing, body
composition assessment, questionnaires, and biomarker sampling when applicable. Cognitive testing
was conducted before intense physical testing to avoid acute fatigue effects on executive performance.
If blood sampling was included, it was performed before physical testing and under standardized
preanalytical conditions.
After baseline testing, participants were randomized and began the 12-week intervention. Attendance,
session RPE, adverse events, and protocol fidelity were recorded throughout the intervention. Midpoint
monitoring occurred around week 6 and included adherence review, safety evaluation, internal load
monitoring, and strength reassessment when appropriate for load adjustment.
markers cannot establish direct brain-level mechanisms in the absence of neuroimaging, cerebrospinal
fluid measures, or more direct neurophysiological methods.
Covariates
Potential covariates included sleep quality, external physical activity, academic stress, caffeine intake,
screen exposure, alcohol use, dietary conditions before testing, menstrual cycle phase when applicable,
time of assessment, and baseline value of the outcome. These covariates were selected because they may
influence executive performance, recovery, perceived exertion, inflammatory status, and body
composition. Covariates were used descriptively and, when methodologically justified, in adjusted
sensitivity models.
Procedure
The study procedure consisted of familiarization, baseline assessment, randomization, 12-week
intervention, midpoint monitoring, posttest assessment, and optional follow-up if retained in the
protocol.
During familiarization, participants received general instructions, practiced cognitive and physical
testing procedures, and were oriented regarding safety, attendance, RPE reporting, and intervention
expectations. Familiarization was included to reduce learning effects, test anxiety, and procedural
variability.
Baseline assessment was conducted before randomization. It included eligibility confirmation,
preassessment condition verification, executive function testing, physical performance testing, body
composition assessment, questionnaires, and biomarker sampling when applicable. Cognitive testing
was conducted before intense physical testing to avoid acute fatigue effects on executive performance.
If blood sampling was included, it was performed before physical testing and under standardized
preanalytical conditions.
After baseline testing, participants were randomized and began the 12-week intervention. Attendance,
session RPE, adverse events, and protocol fidelity were recorded throughout the intervention. Midpoint
monitoring occurred around week 6 and included adherence review, safety evaluation, internal load
monitoring, and strength reassessment when appropriate for load adjustment.
pág. 4556
Posttest assessment was conducted after completion of the 12-week intervention. Whenever possible,
posttest measurements were scheduled 48 to 72 hours after the final training session to reduce the
influence of acute fatigue, delayed-onset muscle soreness, and transient inflammatory responses. The
same testing order and standardized procedures used at baseline were repeated at posttest.
Data Analysis Strategy
Analyses were planned according to the pilot nature of the study. First, feasibility indicators were
described using frequencies, percentages, means, standard deviations, and 95% confidence intervals
when appropriate. Retention, adherence, data completeness, fidelity, acceptability, and adverse events
were interpreted as the primary analytical layer.
Second, baseline characteristics were summarized by group. Continuous variables were reported as
means and standard deviations when approximately normally distributed, or as medians and interquartile
ranges when distributional assumptions were not appropriate. Categorical variables were reported as
frequencies and percentages. Baseline comparisons were treated descriptively and were not interpreted
as formal equivalence tests.
Third, preliminary intervention effects were estimated using linear mixed models with fixed effects for
group, time, and the group-by-time interaction, and with participant-level random intercepts when model
assumptions allowed. The group-by-time interaction was the main term of interest for preliminary
signals in executive function, physical outcomes, body composition, and biomarkers. When appropriate,
ANCOVA sensitivity models were conducted using posttest values adjusted for baseline values, age,
and sex.
Fourth, analyses were conducted using both intention-to-treat and per-protocol perspectives. The
intention-to-treat approach included all randomized participants according to original allocation, using
all available data. The per-protocol analysis included participants who met the predefined adherence
criteria and completed relevant posttest assessments. Complete-case analyses were used for outcomes
requiring both baseline and posttest measures.
Fifth, effect sizes were emphasized because pilot trials should estimate direction, magnitude, variability,
and precision rather than rely exclusively on statistical significance. For pretest-posttest-control group
comparisons, standardized effect sizes were interpreted with reference to the approach described by
Posttest assessment was conducted after completion of the 12-week intervention. Whenever possible,
posttest measurements were scheduled 48 to 72 hours after the final training session to reduce the
influence of acute fatigue, delayed-onset muscle soreness, and transient inflammatory responses. The
same testing order and standardized procedures used at baseline were repeated at posttest.
Data Analysis Strategy
Analyses were planned according to the pilot nature of the study. First, feasibility indicators were
described using frequencies, percentages, means, standard deviations, and 95% confidence intervals
when appropriate. Retention, adherence, data completeness, fidelity, acceptability, and adverse events
were interpreted as the primary analytical layer.
Second, baseline characteristics were summarized by group. Continuous variables were reported as
means and standard deviations when approximately normally distributed, or as medians and interquartile
ranges when distributional assumptions were not appropriate. Categorical variables were reported as
frequencies and percentages. Baseline comparisons were treated descriptively and were not interpreted
as formal equivalence tests.
Third, preliminary intervention effects were estimated using linear mixed models with fixed effects for
group, time, and the group-by-time interaction, and with participant-level random intercepts when model
assumptions allowed. The group-by-time interaction was the main term of interest for preliminary
signals in executive function, physical outcomes, body composition, and biomarkers. When appropriate,
ANCOVA sensitivity models were conducted using posttest values adjusted for baseline values, age,
and sex.
Fourth, analyses were conducted using both intention-to-treat and per-protocol perspectives. The
intention-to-treat approach included all randomized participants according to original allocation, using
all available data. The per-protocol analysis included participants who met the predefined adherence
criteria and completed relevant posttest assessments. Complete-case analyses were used for outcomes
requiring both baseline and posttest measures.
Fifth, effect sizes were emphasized because pilot trials should estimate direction, magnitude, variability,
and precision rather than rely exclusively on statistical significance. For pretest-posttest-control group
comparisons, standardized effect sizes were interpreted with reference to the approach described by
pág. 4557
Morris (2008), which supports estimating the difference in pre-post changes between intervention and
control groups using the pooled pretest standard deviation. Hedges-corrected standardized mean
differences and 95% confidence intervals were reported for main outcomes when appropriate.
Sixth, exploratory association analyses were conducted to examine whether changes in physical
performance, body composition, internal load, or peripheral biomarkers were associated with changes
in executive function. Pearson or Spearman correlations were selected according to distributional
properties, and partial correlations adjusted for group, age, and sex were used as sensitivity analyses.
Regression, mediation, and moderation models were interpreted as exploratory and hypothesis-
generating only. Multiple comparisons were handled through domain-level interpretation, cautious
reporting, and false discovery rate procedures when appropriate.
Ethical Considerations
The study required review and approval by an institutional research ethics committee before recruitment.
Participation was voluntary and required written informed consent. Participants were informed about
the purpose of the study, randomization, intervention procedures, possible risks, potential benefits,
confidentiality, data protection, and their right to withdraw without academic or institutional
consequences.
Ethical procedures were aligned with the Declaration of Helsinki, which establishes principles for
research involving human participants, including respect for autonomy, protection of dignity, informed
consent, risk-benefit assessment, privacy, and scientific transparency (World Medical Association,
2025). In the Mexican context, the study also followed the ethical and methodological criteria
established by NOM-012-SSA3-2012 for health research projects involving human beings (Secretaría
de Salud, 2013).
RESULTS AND DISCUSSION
Participant Flow and Baseline Characteristics
A total of 75 candidates were assessed for eligibility. Fifteen were excluded before randomization, and
60 participants were randomized in a 1:1:1 ratio to linear periodization, undulating periodization, or
active control. Each group included 20 participants at allocation. One participant per group was
unavailable for posttest assessment, resulting in 57 complete-case posttest records. The intention-to-
Morris (2008), which supports estimating the difference in pre-post changes between intervention and
control groups using the pooled pretest standard deviation. Hedges-corrected standardized mean
differences and 95% confidence intervals were reported for main outcomes when appropriate.
Sixth, exploratory association analyses were conducted to examine whether changes in physical
performance, body composition, internal load, or peripheral biomarkers were associated with changes
in executive function. Pearson or Spearman correlations were selected according to distributional
properties, and partial correlations adjusted for group, age, and sex were used as sensitivity analyses.
Regression, mediation, and moderation models were interpreted as exploratory and hypothesis-
generating only. Multiple comparisons were handled through domain-level interpretation, cautious
reporting, and false discovery rate procedures when appropriate.
Ethical Considerations
The study required review and approval by an institutional research ethics committee before recruitment.
Participation was voluntary and required written informed consent. Participants were informed about
the purpose of the study, randomization, intervention procedures, possible risks, potential benefits,
confidentiality, data protection, and their right to withdraw without academic or institutional
consequences.
Ethical procedures were aligned with the Declaration of Helsinki, which establishes principles for
research involving human participants, including respect for autonomy, protection of dignity, informed
consent, risk-benefit assessment, privacy, and scientific transparency (World Medical Association,
2025). In the Mexican context, the study also followed the ethical and methodological criteria
established by NOM-012-SSA3-2012 for health research projects involving human beings (Secretaría
de Salud, 2013).
RESULTS AND DISCUSSION
Participant Flow and Baseline Characteristics
A total of 75 candidates were assessed for eligibility. Fifteen were excluded before randomization, and
60 participants were randomized in a 1:1:1 ratio to linear periodization, undulating periodization, or
active control. Each group included 20 participants at allocation. One participant per group was
unavailable for posttest assessment, resulting in 57 complete-case posttest records. The intention-to-
pág. 4558
treat population included all randomized participants (n = 60), whereas the per-protocol population
included 54 participants who met the predefined adherence criteria.
One participant per group was unavailable for posttest assessment, resulting in 57 complete-case posttest
records. The intention-to-treat analysis included all randomized participants (n = 60), whereas the per-
protocol analysis included participants who met the adherence criterion: linear periodization, n = 19;
undulating periodization, n = 17; and active control, n = 18. Complete case analysis included participants
with valid pretest and posttest data; per-protocol analysis included participants meeting the predefined
adherence criterion.
The overall study sequence, measurement schedule, and intervention timeline are presented in Figure 1.
This figure describes the methodological structure of the trial, including familiarization, baseline testing,
randomization, the 12-week intervention, midpoint monitoring, and posttest assessment.
treat population included all randomized participants (n = 60), whereas the per-protocol population
included 54 participants who met the predefined adherence criteria.
One participant per group was unavailable for posttest assessment, resulting in 57 complete-case posttest
records. The intention-to-treat analysis included all randomized participants (n = 60), whereas the per-
protocol analysis included participants who met the adherence criterion: linear periodization, n = 19;
undulating periodization, n = 17; and active control, n = 18. Complete case analysis included participants
with valid pretest and posttest data; per-protocol analysis included participants meeting the predefined
adherence criterion.
The overall study sequence, measurement schedule, and intervention timeline are presented in Figure 1.
This figure describes the methodological structure of the trial, including familiarization, baseline testing,
randomization, the 12-week intervention, midpoint monitoring, and posttest assessment.
pág. 4559
Figure 1
Study Design, Measurement Schedule, and Intervention Timeline
Note. The figure summarizes the methodological structure of the pilot randomized controlled trial. After familiarization and
baseline assessment, participants were randomized in a 1:1:1 ratio to linear periodization, undulating periodization, or active
control.
The intervention lasted 12 weeks, with midpoint monitoring in week 6 and post test assessment in week
12. Executive function, physical performance, body composition, and peripheral biomarkers were
assessed at baseline and posttest; estimated strength and feasibility indicators were monitored at
midpoint. Biomarkers should be collected 48 to 72 h after the final session to reduce the influence of
acute exercise responses.
Figure 1 should be interpreted as a design and procedural figure rather than as an outcome figure. Its
role is to clarify when each assessment occurred and how the three parallel arms were organized across
the intervention period. This is important for the interpretation of the results because the cognitive,
physical, morphological, and biomarker outcomes were not measured in isolation; they were embedded
in a controlled timeline that included pretest standardization, supervised exposure, midpoint monitoring,
and posttest assessment after the intervention. The figure also reinforces the methodological distinction
between the two resistance training groups and the active control condition before the reader examines
weekly load, executive function, physical adaptation, and biomarker results.
Figure 1
Study Design, Measurement Schedule, and Intervention Timeline
Note. The figure summarizes the methodological structure of the pilot randomized controlled trial. After familiarization and
baseline assessment, participants were randomized in a 1:1:1 ratio to linear periodization, undulating periodization, or active
control.
The intervention lasted 12 weeks, with midpoint monitoring in week 6 and post test assessment in week
12. Executive function, physical performance, body composition, and peripheral biomarkers were
assessed at baseline and posttest; estimated strength and feasibility indicators were monitored at
midpoint. Biomarkers should be collected 48 to 72 h after the final session to reduce the influence of
acute exercise responses.
Figure 1 should be interpreted as a design and procedural figure rather than as an outcome figure. Its
role is to clarify when each assessment occurred and how the three parallel arms were organized across
the intervention period. This is important for the interpretation of the results because the cognitive,
physical, morphological, and biomarker outcomes were not measured in isolation; they were embedded
in a controlled timeline that included pretest standardization, supervised exposure, midpoint monitoring,
and posttest assessment after the intervention. The figure also reinforces the methodological distinction
between the two resistance training groups and the active control condition before the reader examines
weekly load, executive function, physical adaptation, and biomarker results.
pág. 4560
Baseline characteristics are presented in Table 1. The groups were balanced in sample size and showed
no relevant differences in sex distribution, N-back accuracy, Trail Making Test B, estimated 1RM,
handgrip strength, countermovement jump, muscle mass, body fat, peripheral biomarkers, sleep quality,
or stress scores. Two baseline differences were observed: age differed across groups (p = .042), and
baseline Stroop performance also differed across groups (p = .044).
Table 1
Baseline Characteristics and Group Comparability of the Analytical Sample
Variable Linear periodization
(n = 20)
Undulating periodization
(n = 20)
Active control
(n = 20) p
Age, years 20.75 ± 2.47 21.40 ± 2.41 22.65 ± 2.18 0.042
Sex,
male/female 08-dic 12-ago 10-oct 0.449
Stroop, ms 638.67 ± 45.29 616.56 ± 64.67 593.65 ± 54.25 0.044
N-back
accuracy 0.76 ± 0.05 0.73 ± 0.08 0.75 ± 0.07 0.456
Trail Making
Test B, s 64.29 ± 13.36 64.84 ± 11.01 62.08 ± 9.44 0.719
Estimated
1RM, kg 89.43 ± 13.23 86.05 ± 10.53 83.62 ± 16.32 0.403
Handgrip
strength, kg 37.14 ± 7.00 36.71 ± 8.05 34.40 ± 6.58 0.427
Countermovem
ent jump, cm 33.14 ± 4.42 32.60 ± 4.36 31.62 ± 4.38 0.55
Muscle mass,
kg 31.91 ± 4.11 32.07 ± 4.01 31.10 ± 3.94 0.719
Body fat, % 23.36 ± 4.04 22.12 ± 4.21 22.44 ± 4.15 0.626
BDNF, ng/mL 15.59 ± 2.84 15.70 ± 2.75 15.19 ± 2.57 0.823
Cathepsin B,
ng/mL 42.60 ± 4.76 42.33 ± 4.45 41.82 ± 4.46 0.86
IGF-1, ng/mL 182.96 ± 21.37 183.84 ± 22.51 181.32 ± 19.63 0.931
IL-6, pg/mL 1.63 ± 0.29 1.68 ± 0.32 1.62 ± 0.33 0.785
C-reactive
protein, mg/L 0.41 ± 0.16 0.42 ± 0.17 0.42 ± 0.16 0.977
PSQI score 6.96 ± 1.44 6.92 ± 1.66 7.06 ± 1.55 0.961
DASS-21 stress
score 18.67 ± 4.10 19.33 ± 4.42 19.22 ± 4.38 0.87
Note. Data are presented as mean ± standard deviation or absolute frequencies. Baseline comparisons were conducted using
one-way ANOVA, Kruskal-Wallis tests, or chi-square tests as appropriate. Baseline comparisons are descriptive and should
not be interpreted as formal equivalence tests. BDNF = brain-derived neurotrophic factor; IGF-1 = insulin-like growth factor
1; IL-6 = interleukin 6; PSQI = Pittsburgh Sleep Quality Index.
The baseline profile indicates that the randomization process generated broadly comparable groups,
although age and baseline Stroop performance should be considered when interpreting subsequent
cognitive models. These differences do not invalidate the pilot design, but they justify the use of adjusted
Baseline characteristics are presented in Table 1. The groups were balanced in sample size and showed
no relevant differences in sex distribution, N-back accuracy, Trail Making Test B, estimated 1RM,
handgrip strength, countermovement jump, muscle mass, body fat, peripheral biomarkers, sleep quality,
or stress scores. Two baseline differences were observed: age differed across groups (p = .042), and
baseline Stroop performance also differed across groups (p = .044).
Table 1
Baseline Characteristics and Group Comparability of the Analytical Sample
Variable Linear periodization
(n = 20)
Undulating periodization
(n = 20)
Active control
(n = 20) p
Age, years 20.75 ± 2.47 21.40 ± 2.41 22.65 ± 2.18 0.042
Sex,
male/female 08-dic 12-ago 10-oct 0.449
Stroop, ms 638.67 ± 45.29 616.56 ± 64.67 593.65 ± 54.25 0.044
N-back
accuracy 0.76 ± 0.05 0.73 ± 0.08 0.75 ± 0.07 0.456
Trail Making
Test B, s 64.29 ± 13.36 64.84 ± 11.01 62.08 ± 9.44 0.719
Estimated
1RM, kg 89.43 ± 13.23 86.05 ± 10.53 83.62 ± 16.32 0.403
Handgrip
strength, kg 37.14 ± 7.00 36.71 ± 8.05 34.40 ± 6.58 0.427
Countermovem
ent jump, cm 33.14 ± 4.42 32.60 ± 4.36 31.62 ± 4.38 0.55
Muscle mass,
kg 31.91 ± 4.11 32.07 ± 4.01 31.10 ± 3.94 0.719
Body fat, % 23.36 ± 4.04 22.12 ± 4.21 22.44 ± 4.15 0.626
BDNF, ng/mL 15.59 ± 2.84 15.70 ± 2.75 15.19 ± 2.57 0.823
Cathepsin B,
ng/mL 42.60 ± 4.76 42.33 ± 4.45 41.82 ± 4.46 0.86
IGF-1, ng/mL 182.96 ± 21.37 183.84 ± 22.51 181.32 ± 19.63 0.931
IL-6, pg/mL 1.63 ± 0.29 1.68 ± 0.32 1.62 ± 0.33 0.785
C-reactive
protein, mg/L 0.41 ± 0.16 0.42 ± 0.17 0.42 ± 0.16 0.977
PSQI score 6.96 ± 1.44 6.92 ± 1.66 7.06 ± 1.55 0.961
DASS-21 stress
score 18.67 ± 4.10 19.33 ± 4.42 19.22 ± 4.38 0.87
Note. Data are presented as mean ± standard deviation or absolute frequencies. Baseline comparisons were conducted using
one-way ANOVA, Kruskal-Wallis tests, or chi-square tests as appropriate. Baseline comparisons are descriptive and should
not be interpreted as formal equivalence tests. BDNF = brain-derived neurotrophic factor; IGF-1 = insulin-like growth factor
1; IL-6 = interleukin 6; PSQI = Pittsburgh Sleep Quality Index.
The baseline profile indicates that the randomization process generated broadly comparable groups,
although age and baseline Stroop performance should be considered when interpreting subsequent
cognitive models. These differences do not invalidate the pilot design, but they justify the use of adjusted
pág. 4561
sensitivity models, particularly ANCOVA models adjusted for baseline values, age, and sex. In pilot
trials, baseline comparisons are best interpreted descriptively rather than as formal equivalence tests.
Therefore, the relevant conclusion is not that groups were statistically identical, but that the baseline
structure was sufficiently coherent to proceed with feasibility and preliminary signal analyses.
Feasibility, Safety, Adherence, Fidelity, and Acceptability
Posttest retention was 95.0% overall, with identical retention in the three groups. Complete posttest data
was available for 57 of 60 randomized participants. The per-protocol population included 90.0% of
randomized participants. Mean adherence across the total sample was 90.28% ± 8.20, and intervention
fidelity was 92.93% ± 2.52. Data completeness was 95.0%.
These findings indicate that the 12-week university-based protocol was feasible under supervised
conditions. The retention, adherence, fidelity, and data completeness values exceeded conventional
progression thresholds for a pilot trial. Importantly, feasibility was not restricted to one intervention
arm; retention was identical across groups, and adherence remained high across all conditions. This
supports the practical viability of implementing structured resistance training and active control sessions
in a university setting.
Safety outcomes were also favorable. No serious adverse events were observed. Seven mild and two
moderate adverse events were recorded, with events concentrated in the resistance training groups and
none observed in the active control condition. This distribution is plausible because the resistance
training arms involved progressive loading and greater neuromuscular demand. However, the absence
of serious adverse events suggests that the intervention was tolerable when supervised and progressed
conservatively.
Acceptability was favorable overall, although it differed between groups (p = .012), with lower
acceptability in the active control condition. This difference is an important implementation finding.
Active control conditions may reduce nonspecific expectancy bias, but participants may perceive them
as less beneficial or less engaging than resistance training. Therefore, future trials should retain the
active control design while improving its perceived relevance, for example by strengthening the
educational component or ensuring that participants understand its scientific purpose.
sensitivity models, particularly ANCOVA models adjusted for baseline values, age, and sex. In pilot
trials, baseline comparisons are best interpreted descriptively rather than as formal equivalence tests.
Therefore, the relevant conclusion is not that groups were statistically identical, but that the baseline
structure was sufficiently coherent to proceed with feasibility and preliminary signal analyses.
Feasibility, Safety, Adherence, Fidelity, and Acceptability
Posttest retention was 95.0% overall, with identical retention in the three groups. Complete posttest data
was available for 57 of 60 randomized participants. The per-protocol population included 90.0% of
randomized participants. Mean adherence across the total sample was 90.28% ± 8.20, and intervention
fidelity was 92.93% ± 2.52. Data completeness was 95.0%.
These findings indicate that the 12-week university-based protocol was feasible under supervised
conditions. The retention, adherence, fidelity, and data completeness values exceeded conventional
progression thresholds for a pilot trial. Importantly, feasibility was not restricted to one intervention
arm; retention was identical across groups, and adherence remained high across all conditions. This
supports the practical viability of implementing structured resistance training and active control sessions
in a university setting.
Safety outcomes were also favorable. No serious adverse events were observed. Seven mild and two
moderate adverse events were recorded, with events concentrated in the resistance training groups and
none observed in the active control condition. This distribution is plausible because the resistance
training arms involved progressive loading and greater neuromuscular demand. However, the absence
of serious adverse events suggests that the intervention was tolerable when supervised and progressed
conservatively.
Acceptability was favorable overall, although it differed between groups (p = .012), with lower
acceptability in the active control condition. This difference is an important implementation finding.
Active control conditions may reduce nonspecific expectancy bias, but participants may perceive them
as less beneficial or less engaging than resistance training. Therefore, future trials should retain the
active control design while improving its perceived relevance, for example by strengthening the
educational component or ensuring that participants understand its scientific purpose.
pág. 4562
Weekly attendance and internal load are presented in Figure 2. Attendance remained stable throughout
the 12-week intervention, whereas session RPE clearly differentiated the active control group from both
resistance training groups.
Figure 2
Weekly Internal Load and Attendance During the Intervention
Note. Bars represent weekly attendance percentage across all scheduled sessions. Lines represent group-specific weekly mean
session RPE with 95% confidence intervals.
Attendance remained stable throughout the 12-week intervention, whereas internal load was clearly
lower in the active control group than in both resistance training groups, with the highest perceived
effort observed in the undulating periodization group across most weeks.
Figure 2 reinforces the feasibility interpretation by showing that weekly attendance was maintained
while internal load followed the expected pattern. The active control group remained at low perceived
exertion, whereas the linear and undulating periodization groups demonstrated substantially higher
perceived effort. This contrast is important because it indicates that the intervention arms were
meaningfully different in training demand while remaining sufficiently tolerable to sustain adherence.
The highest perceived effort was observed in the undulating periodization group across most weeks,
which should be considered when interpreting differences in outcomes between the two resistance
training models.
Intervention Exposure and Load Progression
Weekly attendance and internal load are presented in Figure 2. Attendance remained stable throughout
the 12-week intervention, whereas session RPE clearly differentiated the active control group from both
resistance training groups.
Figure 2
Weekly Internal Load and Attendance During the Intervention
Note. Bars represent weekly attendance percentage across all scheduled sessions. Lines represent group-specific weekly mean
session RPE with 95% confidence intervals.
Attendance remained stable throughout the 12-week intervention, whereas internal load was clearly
lower in the active control group than in both resistance training groups, with the highest perceived
effort observed in the undulating periodization group across most weeks.
Figure 2 reinforces the feasibility interpretation by showing that weekly attendance was maintained
while internal load followed the expected pattern. The active control group remained at low perceived
exertion, whereas the linear and undulating periodization groups demonstrated substantially higher
perceived effort. This contrast is important because it indicates that the intervention arms were
meaningfully different in training demand while remaining sufficiently tolerable to sustain adherence.
The highest perceived effort was observed in the undulating periodization group across most weeks,
which should be considered when interpreting differences in outcomes between the two resistance
training models.
Intervention Exposure and Load Progression
pág. 4563
Intervention exposure and accumulated training dose are reported in Table 3. The number of sessions
attended did not differ significantly between groups (p = .357), indicating comparable attendance
exposure. However, accumulated training volume, accumulated internal load, mean session RPE, and
RPE area under the curve differed clearly between conditions (all p < .001 for load-related indicators).
The linear periodization group accumulated 241,526.12 ± 40,811.47 kg of external volume, whereas the
undulating periodization group accumulated 226,767.07 ± 36,967.08 kg. The active control group had
no comparable progressive external resistance volume. Conversely, accumulated internal load was
higher in the undulating group (12,400.07 ± 1,270.77) than in the linear group (11,358.16 ± 1,046.35),
and both were higher than active control (3,833.19 ± 410.91).
Table 2
Intervention Exposure, Internal Load, and Accumulated Training Dose
Indicator Linear periodization Undulating
periodization Active control p
Attended sessions 33.20 ± 2.55 32.45 ± 3.05 31.85 ± 3.22 0.357
Adherence, % 92.22 ± 7.07 90.14 ± 8.48 88.47 ± 8.93 0.357
Accumulated volume,
kg
241,526.12 ±
40,811.47 226,767.07 ± 36,967.08 0.00 ± 0.00 <
.001
Accumulated internal
load 11,358.16 ± 1,046.35 12,400.07 ± 1,270.77 3,833.19 ±
410.91
<
.001
Mean session RPE 6.24 ± 0.12 6.93 ± 0.12 2.19 ± 0.04 <
.001
RPE area under the
curve 67.76 ± 4.88 75.50 ± 3.76 23.70 ± 2.02 <
.001
Note. RPE = rating of perceived exertion. Accumulated volume was calculated only for resistance training exercises; therefore,
the active control group was not exposed to progressive external load. The active control condition is retained in the table to
show differential exposure and internal load.
The exposure profile confirms that the study successfully generated two distinct resistance training
conditions and a low-load active control condition. The comparison between linear and undulating
periodization should therefore not be interpreted as a simple comparison of training versus no training.
Both resistance training groups received supervised, progressive, multiweek exposure. Their difference
lies in the temporal organization of load and internal effort. The linear model accumulated slightly
greater external volume, whereas the undulating model produced greater perceived internal load. This
Intervention exposure and accumulated training dose are reported in Table 3. The number of sessions
attended did not differ significantly between groups (p = .357), indicating comparable attendance
exposure. However, accumulated training volume, accumulated internal load, mean session RPE, and
RPE area under the curve differed clearly between conditions (all p < .001 for load-related indicators).
The linear periodization group accumulated 241,526.12 ± 40,811.47 kg of external volume, whereas the
undulating periodization group accumulated 226,767.07 ± 36,967.08 kg. The active control group had
no comparable progressive external resistance volume. Conversely, accumulated internal load was
higher in the undulating group (12,400.07 ± 1,270.77) than in the linear group (11,358.16 ± 1,046.35),
and both were higher than active control (3,833.19 ± 410.91).
Table 2
Intervention Exposure, Internal Load, and Accumulated Training Dose
Indicator Linear periodization Undulating
periodization Active control p
Attended sessions 33.20 ± 2.55 32.45 ± 3.05 31.85 ± 3.22 0.357
Adherence, % 92.22 ± 7.07 90.14 ± 8.48 88.47 ± 8.93 0.357
Accumulated volume,
kg
241,526.12 ±
40,811.47 226,767.07 ± 36,967.08 0.00 ± 0.00 <
.001
Accumulated internal
load 11,358.16 ± 1,046.35 12,400.07 ± 1,270.77 3,833.19 ±
410.91
<
.001
Mean session RPE 6.24 ± 0.12 6.93 ± 0.12 2.19 ± 0.04 <
.001
RPE area under the
curve 67.76 ± 4.88 75.50 ± 3.76 23.70 ± 2.02 <
.001
Note. RPE = rating of perceived exertion. Accumulated volume was calculated only for resistance training exercises; therefore,
the active control group was not exposed to progressive external load. The active control condition is retained in the table to
show differential exposure and internal load.
The exposure profile confirms that the study successfully generated two distinct resistance training
conditions and a low-load active control condition. The comparison between linear and undulating
periodization should therefore not be interpreted as a simple comparison of training versus no training.
Both resistance training groups received supervised, progressive, multiweek exposure. Their difference
lies in the temporal organization of load and internal effort. The linear model accumulated slightly
greater external volume, whereas the undulating model produced greater perceived internal load. This
pág. 4564
distinction is central because some outcome differences may reflect the subjective and neuromuscular
demands of load variation rather than total external volume alone.
Weekly training volume for the two resistance training groups is shown in Figure 3. The active control
group is not shown because it did not complete progressive resistance training with comparable external
load.
Figure 3
Weekly Training Volume in Linear and Undulating Periodization
Note. Lines represent weekly mean training volume (kg) per participant for the two resistance training groups; error bars
indicate 95% confidence intervals.
The active control group is not shown because it did not perform progressive resistance training with
comparable external load. This figure is intended to describe the temporal organization of training load
and should not be interpreted as evidence that one periodization model was superior solely based on
volume.
Figure 3 illustrates the intended temporal contrast between the two periodization structures. The linear
periodization condition displayed a more sequential progression of training volume, whereas the
undulating condition showed a more variable weekly pattern. The figure should not be interpreted as
evidence that one model was superior because of volume alone. Rather, it documents that the two
resistance training programs were organized differently over time, which is necessary for interpreting
subsequent executive, physical, morphological, and biomarker outcomes.
Executive Function Outcomes
distinction is central because some outcome differences may reflect the subjective and neuromuscular
demands of load variation rather than total external volume alone.
Weekly training volume for the two resistance training groups is shown in Figure 3. The active control
group is not shown because it did not complete progressive resistance training with comparable external
load.
Figure 3
Weekly Training Volume in Linear and Undulating Periodization
Note. Lines represent weekly mean training volume (kg) per participant for the two resistance training groups; error bars
indicate 95% confidence intervals.
The active control group is not shown because it did not perform progressive resistance training with
comparable external load. This figure is intended to describe the temporal organization of training load
and should not be interpreted as evidence that one periodization model was superior solely based on
volume.
Figure 3 illustrates the intended temporal contrast between the two periodization structures. The linear
periodization condition displayed a more sequential progression of training volume, whereas the
undulating condition showed a more variable weekly pattern. The figure should not be interpreted as
evidence that one model was superior because of volume alone. Rather, it documents that the two
resistance training programs were organized differently over time, which is necessary for interpreting
subsequent executive, physical, morphological, and biomarker outcomes.
Executive Function Outcomes
pág. 4565
Preliminary changes in executive function outcomes are summarized in Table 3 and visualized in Figure
3. For Stroop and Trail Making Test B, negative change values indicate improvement because they
represent shorter response or completion time. For N-back accuracy, positive change values indicate
improvement.
Table 3
Preliminary Changes in Executive Function Outcomes by Group
Outcome
Active control
Δ M ± SD
Linear
periodization Δ M
± SD
Undulating
periodization
Δ M ± SD
F
chang
e
p ηp²
Stroop, ms
-9.88 ±
10.91
-28.67 ± 14.48 -30.70 ± 13.79 14.49 < .001 0.349
N-back
accuracy
0.02 ± 0.02 0.05 ± 0.02 0.08 ± 0.02 37.68 < .001 0.583
Trail Making
Test B, s
-0.72 ± 2.02 -7.18 ± 2.60 -8.78 ± 2.35 63.57 < .001 0.702
Note. Δ = posttest minus pretest. For Stroop and Trail Making Test B, negative values indicate improvement because they
represent reduced completion or response time. For N-back accuracy, positive values indicate improvement. ηp² = partial eta
squared.
The active control group showed a mean Stroop change of -9.88 ± 10.91 ms, whereas the linear and
undulating periodization groups showed larger reductions of -28.67 ± 14.48 ms and -30.70 ± 13.79 ms,
respectively. The group difference in change was significant, F = 14.49, p < .001, ηp² = .349. N-back
accuracy increased by 0.02 ± 0.02 in the active control group, 0.05 ± 0.02 in the linear group, and 0.08
± 0.02 in the undulating group, with a significant group difference, F = 37.68, p < .001, ηp² = .583. Trail
Making Test B performance improved minimally in the active control group (-0.72 ± 2.02 s) but showed
larger reductions in the linear (-7.18 ± 2.60 s) and undulating (-8.78 ± 2.35 s) groups, F = 63.57, p <
.001, ηp² = .702.
Figure 4
Executive Function Changes by Group
Preliminary changes in executive function outcomes are summarized in Table 3 and visualized in Figure
3. For Stroop and Trail Making Test B, negative change values indicate improvement because they
represent shorter response or completion time. For N-back accuracy, positive change values indicate
improvement.
Table 3
Preliminary Changes in Executive Function Outcomes by Group
Outcome
Active control
Δ M ± SD
Linear
periodization Δ M
± SD
Undulating
periodization
Δ M ± SD
F
chang
e
p ηp²
Stroop, ms
-9.88 ±
10.91
-28.67 ± 14.48 -30.70 ± 13.79 14.49 < .001 0.349
N-back
accuracy
0.02 ± 0.02 0.05 ± 0.02 0.08 ± 0.02 37.68 < .001 0.583
Trail Making
Test B, s
-0.72 ± 2.02 -7.18 ± 2.60 -8.78 ± 2.35 63.57 < .001 0.702
Note. Δ = posttest minus pretest. For Stroop and Trail Making Test B, negative values indicate improvement because they
represent reduced completion or response time. For N-back accuracy, positive values indicate improvement. ηp² = partial eta
squared.
The active control group showed a mean Stroop change of -9.88 ± 10.91 ms, whereas the linear and
undulating periodization groups showed larger reductions of -28.67 ± 14.48 ms and -30.70 ± 13.79 ms,
respectively. The group difference in change was significant, F = 14.49, p < .001, ηp² = .349. N-back
accuracy increased by 0.02 ± 0.02 in the active control group, 0.05 ± 0.02 in the linear group, and 0.08
± 0.02 in the undulating group, with a significant group difference, F = 37.68, p < .001, ηp² = .583. Trail
Making Test B performance improved minimally in the active control group (-0.72 ± 2.02 s) but showed
larger reductions in the linear (-7.18 ± 2.60 s) and undulating (-8.78 ± 2.35 s) groups, F = 63.57, p <
.001, ηp² = .702.
Figure 4
Executive Function Changes by Group
pág. 4566
Note. The figure shows mean change scores with 95% confidence intervals for executive function outcomes across groups.
Panel A presents Δ Stroop (ms), Panel B presents Δ N-back accuracy, and Panel C presents Δ TMT-B (s).
Negative changes indicate improvement for Stroop and TMT-B because they represent reduced response
or completion time, whereas positive changes indicate improvement for N-back accuracy. Values were
calculated from complete posttest cases and are fully consistent with the analytical matrix and the results
reported in Table 3.
Figure 3 provides a visual synthesis of the cognitive pattern. Both resistance training groups
demonstrated more favorable changes than active control across inhibitory control, working memory,
and cognitive flexibility. The largest separation was observed for Trail Making Test B and N-back
accuracy, while Stroop also showed a consistent favorable direction. The undulating group showed
numerically greater gains than the linear group in N-back accuracy and Trail Making Test B, although
the pilot design does not justify a definitive claim of superiority. These findings should be interpreted
as preliminary functional signals that support progression to a larger trial, not as conclusive evidence of
cognitive efficacy.
From an interpretive standpoint, the convergence across the three executive outcomes is more important
than any single p value. The findings suggest that a 12-week periodized resistance training protocol may
be associated with improvements in cognitive domains relevant to attention, working memory updating,
and cognitive flexibility in university students. However, because practice effects, expectancy, sleep,
stress, and baseline cognitive differences can influence executive task performance, the results require
replication in a fully powered trial with stronger control of covariates and preregistered cognitive
endpoints.
Physical and Morphological Adaptations
Note. The figure shows mean change scores with 95% confidence intervals for executive function outcomes across groups.
Panel A presents Δ Stroop (ms), Panel B presents Δ N-back accuracy, and Panel C presents Δ TMT-B (s).
Negative changes indicate improvement for Stroop and TMT-B because they represent reduced response
or completion time, whereas positive changes indicate improvement for N-back accuracy. Values were
calculated from complete posttest cases and are fully consistent with the analytical matrix and the results
reported in Table 3.
Figure 3 provides a visual synthesis of the cognitive pattern. Both resistance training groups
demonstrated more favorable changes than active control across inhibitory control, working memory,
and cognitive flexibility. The largest separation was observed for Trail Making Test B and N-back
accuracy, while Stroop also showed a consistent favorable direction. The undulating group showed
numerically greater gains than the linear group in N-back accuracy and Trail Making Test B, although
the pilot design does not justify a definitive claim of superiority. These findings should be interpreted
as preliminary functional signals that support progression to a larger trial, not as conclusive evidence of
cognitive efficacy.
From an interpretive standpoint, the convergence across the three executive outcomes is more important
than any single p value. The findings suggest that a 12-week periodized resistance training protocol may
be associated with improvements in cognitive domains relevant to attention, working memory updating,
and cognitive flexibility in university students. However, because practice effects, expectancy, sleep,
stress, and baseline cognitive differences can influence executive task performance, the results require
replication in a fully powered trial with stronger control of covariates and preregistered cognitive
endpoints.
Physical and Morphological Adaptations
pág. 4567
Physical and morphological outcomes are presented in Table 4 and Figure 5. The resistance training
groups showed larger preliminary improvements than active control in estimated maximal strength,
handgrip strength, countermovement jump, muscle mass, and body fat percentage.
Table 4
Preliminary Changes in Strength, Neuromuscular Performance, and Body Composition
Outcome
Active control
Δ M ± SD
Linear
periodization
Δ M ± SD
Undulating
periodization Δ
M ± SD
F change p ηp²
Estimated 1RM,
kg
3.46 ± 2.75 13.30 ± 3.01 16.34 ± 2.68 108.42 < .001 0.801
Handgrip
strength, kg
-0.17 ± 0.85 2.59 ± 0.78 2.37 ± 0.91 61.7 < .001 0.696
Countermovement
jump, cm
0.41 ± 0.77 2.26 ± 0.91 3.33 ± 0.79 60.91 < .001 0.693
Muscle mass, kg -0.07 ± 0.26 1.07 ± 0.37 1.28 ± 0.43 76.65 < .001 0.74
Body fat, % -0.18 ± 0.30 -0.95 ± 0.34 -1.34 ± 0.30 66.71 < .001 0.712
Note. Δ = posttest minus pretest. Positive values indicate improvement for estimated 1RM, handgrip strength,
countermovement jump, and muscle mass. Negative values indicate favorable reduction for body fat percentage. 1RM = one-
repetition maximum; ηp² = partial eta squared.
Estimated 1RM increased by 3.46 ± 2.75 kg in the active control group, 13.30 ± 3.01 kg in the linear
periodization group, and 16.34 ± 2.68 kg in the undulating periodization group, F = 108.42, p < .001,
ηp² = .801. Handgrip strength changed by -0.17 ± 0.85 kg in active control, 2.59 ± 0.78 kg in linear
periodization, and 2.37 ± 0.91 kg in undulating periodization, F = 61.70, p < .001, ηp² = .696.
Countermovement jump increased by 0.41 ± 0.77 cm, 2.26 ± 0.91 cm, and 3.33 ± 0.79 cm in active
control, linear, and undulating groups, respectively, F = 60.91, p < .001, ηp² = .693.
Muscle mass showed a small negative change in active control (-0.07 ± 0.26 kg), while increasing in the
linear (1.07 ± 0.37 kg) and undulating (1.28 ± 0.43 kg) periodization groups, F = 76.65, p < .001, ηp² =
.740. Body fat percentage decreased across groups, but the reduction was larger in the resistance training
Physical and morphological outcomes are presented in Table 4 and Figure 5. The resistance training
groups showed larger preliminary improvements than active control in estimated maximal strength,
handgrip strength, countermovement jump, muscle mass, and body fat percentage.
Table 4
Preliminary Changes in Strength, Neuromuscular Performance, and Body Composition
Outcome
Active control
Δ M ± SD
Linear
periodization
Δ M ± SD
Undulating
periodization Δ
M ± SD
F change p ηp²
Estimated 1RM,
kg
3.46 ± 2.75 13.30 ± 3.01 16.34 ± 2.68 108.42 < .001 0.801
Handgrip
strength, kg
-0.17 ± 0.85 2.59 ± 0.78 2.37 ± 0.91 61.7 < .001 0.696
Countermovement
jump, cm
0.41 ± 0.77 2.26 ± 0.91 3.33 ± 0.79 60.91 < .001 0.693
Muscle mass, kg -0.07 ± 0.26 1.07 ± 0.37 1.28 ± 0.43 76.65 < .001 0.74
Body fat, % -0.18 ± 0.30 -0.95 ± 0.34 -1.34 ± 0.30 66.71 < .001 0.712
Note. Δ = posttest minus pretest. Positive values indicate improvement for estimated 1RM, handgrip strength,
countermovement jump, and muscle mass. Negative values indicate favorable reduction for body fat percentage. 1RM = one-
repetition maximum; ηp² = partial eta squared.
Estimated 1RM increased by 3.46 ± 2.75 kg in the active control group, 13.30 ± 3.01 kg in the linear
periodization group, and 16.34 ± 2.68 kg in the undulating periodization group, F = 108.42, p < .001,
ηp² = .801. Handgrip strength changed by -0.17 ± 0.85 kg in active control, 2.59 ± 0.78 kg in linear
periodization, and 2.37 ± 0.91 kg in undulating periodization, F = 61.70, p < .001, ηp² = .696.
Countermovement jump increased by 0.41 ± 0.77 cm, 2.26 ± 0.91 cm, and 3.33 ± 0.79 cm in active
control, linear, and undulating groups, respectively, F = 60.91, p < .001, ηp² = .693.
Muscle mass showed a small negative change in active control (-0.07 ± 0.26 kg), while increasing in the
linear (1.07 ± 0.37 kg) and undulating (1.28 ± 0.43 kg) periodization groups, F = 76.65, p < .001, ηp² =
.740. Body fat percentage decreased across groups, but the reduction was larger in the resistance training
pág. 4568
groups: -0.18 ± 0.30% in active control, -0.95 ± 0.34% in linear periodization, and -1.34 ± 0.30% in
undulating periodization, F = 66.71, p < .001, ηp² = .712.
Figure 5
Physical and Morphological Adaptations by Group
Note. The figure shows mean change scores with 95% confidence intervals for physical and morphological outcomes across
groups.
Panel A presents Δ Estimated 1RM (kg), Panel B presents Δ Countermovement Jump (cm), Panel C
presents Δ Muscle Mass (kg), and Panel D presents Δ Body Fat (%). Positive changes indicate
improvement for estimated 1RM, countermovement jump, and muscle mass, whereas negative changes
indicate favorable reduction for body fat percentage. Values were calculated from complete posttest
cases and are fully consistent with the analytical matrix and the results reported in Table 5.
Figure 5 shows that the physical and morphological outcomes followed a coherent adaptation pattern.
The resistance training groups improved strength, neuromuscular performance, and body composition
more than active control. This is important because the cognitive and biomarker findings should be
interpreted only after confirming that the resistance training intervention produced measurable physical
adaptation. In other words, the intervention was not merely a supervised activity exposure; it generated
objective physiological and performance-related changes consistent with resistance training adaptation.
The physical findings also clarify the interpretation of periodization. The undulating group showed
numerically larger changes in estimated 1RM, countermovement jump, muscle mass, and body fat
reduction, whereas the linear group showed slightly higher handgrip improvement. This mixed pattern
groups: -0.18 ± 0.30% in active control, -0.95 ± 0.34% in linear periodization, and -1.34 ± 0.30% in
undulating periodization, F = 66.71, p < .001, ηp² = .712.
Figure 5
Physical and Morphological Adaptations by Group
Note. The figure shows mean change scores with 95% confidence intervals for physical and morphological outcomes across
groups.
Panel A presents Δ Estimated 1RM (kg), Panel B presents Δ Countermovement Jump (cm), Panel C
presents Δ Muscle Mass (kg), and Panel D presents Δ Body Fat (%). Positive changes indicate
improvement for estimated 1RM, countermovement jump, and muscle mass, whereas negative changes
indicate favorable reduction for body fat percentage. Values were calculated from complete posttest
cases and are fully consistent with the analytical matrix and the results reported in Table 5.
Figure 5 shows that the physical and morphological outcomes followed a coherent adaptation pattern.
The resistance training groups improved strength, neuromuscular performance, and body composition
more than active control. This is important because the cognitive and biomarker findings should be
interpreted only after confirming that the resistance training intervention produced measurable physical
adaptation. In other words, the intervention was not merely a supervised activity exposure; it generated
objective physiological and performance-related changes consistent with resistance training adaptation.
The physical findings also clarify the interpretation of periodization. The undulating group showed
numerically larger changes in estimated 1RM, countermovement jump, muscle mass, and body fat
reduction, whereas the linear group showed slightly higher handgrip improvement. This mixed pattern
pág. 4569
does not support a simplistic claim that one model was universally superior. Rather, it suggests that
different adaptation domains may respond differently to the temporal organization of load.
Peripheral Biomarker Outcomes
Changes in peripheral biomarkers are summarized in Table 5. The biomarker analyses were exploratory
and were interpreted as peripheral systemic signals rather than direct evidence of central neuroplasticity.
does not support a simplistic claim that one model was universally superior. Rather, it suggests that
different adaptation domains may respond differently to the temporal organization of load.
Peripheral Biomarker Outcomes
Changes in peripheral biomarkers are summarized in Table 5. The biomarker analyses were exploratory
and were interpreted as peripheral systemic signals rather than direct evidence of central neuroplasticity.
pág. 4570
Table 5
Peripheral Biomarker Changes and Log-Transformed Sensitivity Analysis
Biomarker
Active
control Δ
M ± SD
Linear
periodization Δ M
± SD
Undulating
periodization Δ M ±
SD
ANCOVA
log p
ηp²
BDNF, ng/mL 0.01 ± 0.92 2.88 ± 1.30 3.83 ± 1.21 < .001 0.69
Cathepsin B,
ng/mL
0.96 ± 2.54 4.36 ± 1.72 4.95 ± 2.39 < .001 0.379
IGF-1, ng/mL 1.74 ± 8.44 14.88 ± 9.35 16.45 ± 8.49 < .001 0.385
IL-6, pg/mL 0.04 ± 0.10 -0.19 ± 0.10 -0.21 ± 0.10 < .001 0.487
C-reactive
protein, mg/L
0.05 ± 0.09 -0.20 ± 0.11 -0.29 ± 0.11 < .001 0.447
Note. Δ = posttest minus pretest. ANCOVA log p refers to the log-transformed posttest model adjusted for log-transformed
baseline value, age, and sex. BDNF = brain-derived neurotrophic factor; IGF-1 = insulin-like growth factor 1; IL-6 = interleukin
6. These biomarkers are interpreted as peripheral exploratory markers and not as direct evidence of central neuroplasticity.
BDNF changed minimally in active control (0.01 ± 0.92 ng/mL), while increasing in the linear (2.88 ±
1.30 ng/mL) and undulating (3.83 ± 1.21 ng/mL) periodization groups. Cathepsin B increased by 0.96
± 2.54 ng/mL in active control, 4.36 ± 1.72 ng/mL in linear periodization, and 4.95 ± 2.39 ng/mL in
undulating periodization. IGF-1 increased by 1.74 ± 8.44 ng/mL in active control, 14.88 ± 9.35 ng/mL
in linear periodization, and 16.45 ± 8.49 ng/mL in undulating periodization. IL-6 increased slightly in
active control (0.04 ± 0.10 pg/mL) but decreased in linear (-0.19 ± 0.10 pg/mL) and undulating (-0.21
± 0.10 pg/mL) periodization. C-reactive protein increased slightly in active control (0.05 ± 0.09 mg/L)
but decreased in linear (-0.20 ± 0.11 mg/L) and undulating (-0.29 ± 0.11 mg/L) periodization. Log-
transformed ANCOVA sensitivity models remained significant for all biomarker outcomes (all p <
.001).
These results are consistent with a favorable peripheral profile in the resistance training groups.
However, they should be interpreted cautiously. Blood-based BDNF, cathepsin B, IGF-1, IL-6, and C-
reactive protein are influenced by multiple biological, behavioral, and preanalytical factors. Therefore,
Table 5
Peripheral Biomarker Changes and Log-Transformed Sensitivity Analysis
Biomarker
Active
control Δ
M ± SD
Linear
periodization Δ M
± SD
Undulating
periodization Δ M ±
SD
ANCOVA
log p
ηp²
BDNF, ng/mL 0.01 ± 0.92 2.88 ± 1.30 3.83 ± 1.21 < .001 0.69
Cathepsin B,
ng/mL
0.96 ± 2.54 4.36 ± 1.72 4.95 ± 2.39 < .001 0.379
IGF-1, ng/mL 1.74 ± 8.44 14.88 ± 9.35 16.45 ± 8.49 < .001 0.385
IL-6, pg/mL 0.04 ± 0.10 -0.19 ± 0.10 -0.21 ± 0.10 < .001 0.487
C-reactive
protein, mg/L
0.05 ± 0.09 -0.20 ± 0.11 -0.29 ± 0.11 < .001 0.447
Note. Δ = posttest minus pretest. ANCOVA log p refers to the log-transformed posttest model adjusted for log-transformed
baseline value, age, and sex. BDNF = brain-derived neurotrophic factor; IGF-1 = insulin-like growth factor 1; IL-6 = interleukin
6. These biomarkers are interpreted as peripheral exploratory markers and not as direct evidence of central neuroplasticity.
BDNF changed minimally in active control (0.01 ± 0.92 ng/mL), while increasing in the linear (2.88 ±
1.30 ng/mL) and undulating (3.83 ± 1.21 ng/mL) periodization groups. Cathepsin B increased by 0.96
± 2.54 ng/mL in active control, 4.36 ± 1.72 ng/mL in linear periodization, and 4.95 ± 2.39 ng/mL in
undulating periodization. IGF-1 increased by 1.74 ± 8.44 ng/mL in active control, 14.88 ± 9.35 ng/mL
in linear periodization, and 16.45 ± 8.49 ng/mL in undulating periodization. IL-6 increased slightly in
active control (0.04 ± 0.10 pg/mL) but decreased in linear (-0.19 ± 0.10 pg/mL) and undulating (-0.21
± 0.10 pg/mL) periodization. C-reactive protein increased slightly in active control (0.05 ± 0.09 mg/L)
but decreased in linear (-0.20 ± 0.11 mg/L) and undulating (-0.29 ± 0.11 mg/L) periodization. Log-
transformed ANCOVA sensitivity models remained significant for all biomarker outcomes (all p <
.001).
These results are consistent with a favorable peripheral profile in the resistance training groups.
However, they should be interpreted cautiously. Blood-based BDNF, cathepsin B, IGF-1, IL-6, and C-
reactive protein are influenced by multiple biological, behavioral, and preanalytical factors. Therefore,
pág. 4571
the biomarker pattern should be described as an exploratory systemic signal compatible with exercise
adaptation, not as proof that resistance training directly produced central neuroplasticity. The biomarker
findings are useful for hypothesis generation and trial planning, particularly if future research includes
stricter laboratory controls, larger samples, and complementary neurophysiological measures.
Standardized Effect Sizes Across Main Outcomes
Standardized effect sizes are shown in Table 6 and Figure 6. Table 6 reports Hedges’ g for the main
outcomes using the original directional meaning of each variable, whereas Figure 6 provides a visual
synthesis of effect magnitude across domains. For lower-is-better outcomes such as Stroop, Trail
Making Test B, body fat, and C-reactive protein, negative values in Table 6 indicate favorable
reductions. For higher-is-better outcomes such as N-back, estimated 1RM, countermovement jump,
muscle mass, and BDNF, positive values indicate favorable increases.
Table 6
Standardized Effect Sizes for Main Outcomes
Outcome Linear vs active control
g [95% CI]
Undulating vs active
control g [95% CI]
Undulating vs linear
g [95% CI]
Δ Stroop -1.44 [-2.15, -0.72] -1.64 [-2.38, -0.90] -0.14 [-0.78, 0.50]
Δ N-back 1.68 [0.93, 2.42] 2.79 [1.89, 3.70] 1.07 [0.39, 1.75]
Δ Trail Making
Test B -2.72 [-3.61, -1.83] -3.61 [-4.66, -2.56] -0.63 [-1.28, 0.02]
Δ Estimated 1RM 3.34 [2.34, 4.34] 4.64 [3.40, 5.89] 1.04 [0.36, 1.72]
Δ
Countermovement
jump
2.15 [1.34, 2.95] 3.66 [2.60, 4.72] 1.24 [0.54, 1.93]
Δ Muscle mass 3.50 [2.47, 4.53] 3.69 [2.63, 4.76] 0.52 [-0.13, 1.16]
Δ Body fat -2.34 [-3.17, -1.50] -3.80 [-4.88, -2.71] -1.18 [-1.88, -0.49]
Δ BDNF 2.50 [1.64, 3.36] 3.49 [2.46, 4.51] 0.74 [0.08, 1.39]
Δ C-reactive
protein -2.43 [-3.27, -1.58] -3.28 [-4.27, -2.29] -0.78 [-1.44, -0.12]
Note. g = Hedges’ g. Negative values indicate favorable reductions for Stroop, Trail Making Test B, body fat, and C-reactive
protein. Positive values indicate favorable increases for N-back, estimated 1RM, countermovement jump, muscle mass, and
BDNF.
the biomarker pattern should be described as an exploratory systemic signal compatible with exercise
adaptation, not as proof that resistance training directly produced central neuroplasticity. The biomarker
findings are useful for hypothesis generation and trial planning, particularly if future research includes
stricter laboratory controls, larger samples, and complementary neurophysiological measures.
Standardized Effect Sizes Across Main Outcomes
Standardized effect sizes are shown in Table 6 and Figure 6. Table 6 reports Hedges’ g for the main
outcomes using the original directional meaning of each variable, whereas Figure 6 provides a visual
synthesis of effect magnitude across domains. For lower-is-better outcomes such as Stroop, Trail
Making Test B, body fat, and C-reactive protein, negative values in Table 6 indicate favorable
reductions. For higher-is-better outcomes such as N-back, estimated 1RM, countermovement jump,
muscle mass, and BDNF, positive values indicate favorable increases.
Table 6
Standardized Effect Sizes for Main Outcomes
Outcome Linear vs active control
g [95% CI]
Undulating vs active
control g [95% CI]
Undulating vs linear
g [95% CI]
Δ Stroop -1.44 [-2.15, -0.72] -1.64 [-2.38, -0.90] -0.14 [-0.78, 0.50]
Δ N-back 1.68 [0.93, 2.42] 2.79 [1.89, 3.70] 1.07 [0.39, 1.75]
Δ Trail Making
Test B -2.72 [-3.61, -1.83] -3.61 [-4.66, -2.56] -0.63 [-1.28, 0.02]
Δ Estimated 1RM 3.34 [2.34, 4.34] 4.64 [3.40, 5.89] 1.04 [0.36, 1.72]
Δ
Countermovement
jump
2.15 [1.34, 2.95] 3.66 [2.60, 4.72] 1.24 [0.54, 1.93]
Δ Muscle mass 3.50 [2.47, 4.53] 3.69 [2.63, 4.76] 0.52 [-0.13, 1.16]
Δ Body fat -2.34 [-3.17, -1.50] -3.80 [-4.88, -2.71] -1.18 [-1.88, -0.49]
Δ BDNF 2.50 [1.64, 3.36] 3.49 [2.46, 4.51] 0.74 [0.08, 1.39]
Δ C-reactive
protein -2.43 [-3.27, -1.58] -3.28 [-4.27, -2.29] -0.78 [-1.44, -0.12]
Note. g = Hedges’ g. Negative values indicate favorable reductions for Stroop, Trail Making Test B, body fat, and C-reactive
protein. Positive values indicate favorable increases for N-back, estimated 1RM, countermovement jump, muscle mass, and
BDNF.
pág. 4572
The effect size pattern favored both resistance training groups overactive control across executive
function, physical performance, morphology, and peripheral biomarkers. For executive function, linear
periodization versus active control showed large, standardized differences for Stroop (g = -1.44), N-
back (g = 1.68), and Trail Making Test B (g = -2.72). Undulating periodization versus active control
showed similarly large or larger differences for Stroop (g = -1.64), N-back (g = 2.79), and Trail Making
Test B (g = -3.61). Physical and morphological outcomes also showed large effects, particularly
estimated 1RM, countermovement jump, muscle mass, and body fat percentage.
Figure 6
Standardized Effect Sizes Across Main Outcomes
Note. Values are Hedges-corrected standardized mean differences for posttest minus pretest change scores versus active control,
standardized by pooled baseline standard deviation.
Positive values favor periodized training. For lower-is-better outcomes, the sign was reversed for
interpretive consistency. The figure integrates executive function, physical performance, morphology,
and peripheral biomarkers.
Figure 6 functions as the main integrative visual summary of the trial. It shows that the strongest
preliminary signals were not isolated to one domain but were distributed across executive function,
The effect size pattern favored both resistance training groups overactive control across executive
function, physical performance, morphology, and peripheral biomarkers. For executive function, linear
periodization versus active control showed large, standardized differences for Stroop (g = -1.44), N-
back (g = 1.68), and Trail Making Test B (g = -2.72). Undulating periodization versus active control
showed similarly large or larger differences for Stroop (g = -1.64), N-back (g = 2.79), and Trail Making
Test B (g = -3.61). Physical and morphological outcomes also showed large effects, particularly
estimated 1RM, countermovement jump, muscle mass, and body fat percentage.
Figure 6
Standardized Effect Sizes Across Main Outcomes
Note. Values are Hedges-corrected standardized mean differences for posttest minus pretest change scores versus active control,
standardized by pooled baseline standard deviation.
Positive values favor periodized training. For lower-is-better outcomes, the sign was reversed for
interpretive consistency. The figure integrates executive function, physical performance, morphology,
and peripheral biomarkers.
Figure 6 functions as the main integrative visual summary of the trial. It shows that the strongest
preliminary signals were not isolated to one domain but were distributed across executive function,
pág. 4573
neuromuscular adaptation, morphology, and selected peripheral biomarkers. This multidomain pattern
strengthens the internal coherence of the pilot findings. However, effect sizes in pilot trials are often
unstable and can be inflated, especially with small samples and optimized adherence. Therefore, these
values should be used primarily to inform the design and sample size estimation of a definitive trial, not
to make confirmatory claims.
Exploratory Associations Between Physical, Biomarker, and Executive Function Changes
Exploratory associations are presented in Table 7. These analyses examined whether changes in physical
adaptation, internal load, and peripheral biomarkers were associated with changes in executive function
outcomes.
Table 7
Exploratory Associations Between Physical, Biomarker, and Executive Function Changes
Predictor Outcome Pearson
r p
Partial r
adjusted
for
group,
age, and
sex
p
adjusted Interpretation
Δ Estimated
1RM Δ N-back 0.705 <
.001 0.159 0.256
Strong bivariate
association attenuated
after adjustment
Δ Estimated
1RM
Δ Trail Making
Test B -0.759 <
.001 -0.054 0.702
Bivariate association
largely explained by
group
Δ Muscle
mass
Δ Trail Making
Test B -0.774 <
.001 -0.174 0.212
Bivariate association
attenuated after
adjustment
Δ BDNF Δ Trail Making
Test B -0.596 <
.001 0.289 0.036 Exploratory peripheral
signal requiring caution
Δ C-reactive
protein Δ N-back -0.731 <
.001 -0.303 0.028 Exploratory inflammatory
signal requiring caution
Accumulated
internal load Δ Estimated 1RM 0.374 0.021 NA NA
Dose-response signal
within resistance training
groups
Accumulated
internal load
Δ
Countermovement
jump
0.255 0.122 NA NA Weak dose-response
tendency
neuromuscular adaptation, morphology, and selected peripheral biomarkers. This multidomain pattern
strengthens the internal coherence of the pilot findings. However, effect sizes in pilot trials are often
unstable and can be inflated, especially with small samples and optimized adherence. Therefore, these
values should be used primarily to inform the design and sample size estimation of a definitive trial, not
to make confirmatory claims.
Exploratory Associations Between Physical, Biomarker, and Executive Function Changes
Exploratory associations are presented in Table 7. These analyses examined whether changes in physical
adaptation, internal load, and peripheral biomarkers were associated with changes in executive function
outcomes.
Table 7
Exploratory Associations Between Physical, Biomarker, and Executive Function Changes
Predictor Outcome Pearson
r p
Partial r
adjusted
for
group,
age, and
sex
p
adjusted Interpretation
Δ Estimated
1RM Δ N-back 0.705 <
.001 0.159 0.256
Strong bivariate
association attenuated
after adjustment
Δ Estimated
1RM
Δ Trail Making
Test B -0.759 <
.001 -0.054 0.702
Bivariate association
largely explained by
group
Δ Muscle
mass
Δ Trail Making
Test B -0.774 <
.001 -0.174 0.212
Bivariate association
attenuated after
adjustment
Δ BDNF Δ Trail Making
Test B -0.596 <
.001 0.289 0.036 Exploratory peripheral
signal requiring caution
Δ C-reactive
protein Δ N-back -0.731 <
.001 -0.303 0.028 Exploratory inflammatory
signal requiring caution
Accumulated
internal load Δ Estimated 1RM 0.374 0.021 NA NA
Dose-response signal
within resistance training
groups
Accumulated
internal load
Δ
Countermovement
jump
0.255 0.122 NA NA Weak dose-response
tendency
pág. 4574
Note. Δ = posttest minus pretest. Negative correlations with Stroop or Trail Making Test B indicate that greater change in the
predictor is associated with greater reduction in time. Partial correlations were adjusted for group, age, and sex. Associations
involving biomarkers should be interpreted as exploratory and not as mechanistic proof.
Several bivariate associations were strong. For example, change in estimated 1RM was positively
associated with change in N-back accuracy (r = .705, p < .001) and negatively associated with change
in Trail Making Test B (r = -.759, p < .001), indicating that greater strength gains were associated with
better working memory and cognitive flexibility performance. Change in muscle mass was also
negatively associated with change in Trail Making Test B (r = -.774, p < .001). In addition, change in
C-reactive protein was negatively associated with N-back accuracy (r = -.731, p < .001), suggesting that
greater reductions in systemic inflammation were associated with greater improvements in working
memory accuracy.
However, most associations were substantially attenuated after adjustment for group, age, and sex. For
instance, the association between change in estimated 1RM and N-back accuracy decreased from r =
.705 to partial r = .159 (p = .256), and the association between change in estimated 1RM and Trail
Making Test B decreased from r = -.759 to partial r = -.054 (p = .702). Two exploratory adjusted
associations remained statistically relevant: BDNF with Trail Making Test B (partial r = .289, p = .036)
and C-reactive protein with N-back accuracy (partial r = -.303, p = .028).
This attenuation is analytically important. It suggests that much of the bivariate relationship between
physical and cognitive change was explained by group allocation rather than by a direct individual-level
association independent of intervention conditions. Therefore, the association analyses should not be
used to claim mediation or mechanism. Their main value is to identify candidate pathways for future
trials with larger samples, stronger mechanistic measures, and preregistered mediation models.
CONCLUSIONS
This randomized pilot trial supports the feasibility, safety, and preliminary analytical stability of
implementing a 12-week university-based resistance training protocol with two distinct periodization
models in young university students. Retention, adherence, intervention fidelity, and data completeness
were high across groups, and no serious adverse events were observed. These findings indicate that
Note. Δ = posttest minus pretest. Negative correlations with Stroop or Trail Making Test B indicate that greater change in the
predictor is associated with greater reduction in time. Partial correlations were adjusted for group, age, and sex. Associations
involving biomarkers should be interpreted as exploratory and not as mechanistic proof.
Several bivariate associations were strong. For example, change in estimated 1RM was positively
associated with change in N-back accuracy (r = .705, p < .001) and negatively associated with change
in Trail Making Test B (r = -.759, p < .001), indicating that greater strength gains were associated with
better working memory and cognitive flexibility performance. Change in muscle mass was also
negatively associated with change in Trail Making Test B (r = -.774, p < .001). In addition, change in
C-reactive protein was negatively associated with N-back accuracy (r = -.731, p < .001), suggesting that
greater reductions in systemic inflammation were associated with greater improvements in working
memory accuracy.
However, most associations were substantially attenuated after adjustment for group, age, and sex. For
instance, the association between change in estimated 1RM and N-back accuracy decreased from r =
.705 to partial r = .159 (p = .256), and the association between change in estimated 1RM and Trail
Making Test B decreased from r = -.759 to partial r = -.054 (p = .702). Two exploratory adjusted
associations remained statistically relevant: BDNF with Trail Making Test B (partial r = .289, p = .036)
and C-reactive protein with N-back accuracy (partial r = -.303, p = .028).
This attenuation is analytically important. It suggests that much of the bivariate relationship between
physical and cognitive change was explained by group allocation rather than by a direct individual-level
association independent of intervention conditions. Therefore, the association analyses should not be
used to claim mediation or mechanism. Their main value is to identify candidate pathways for future
trials with larger samples, stronger mechanistic measures, and preregistered mediation models.
CONCLUSIONS
This randomized pilot trial supports the feasibility, safety, and preliminary analytical stability of
implementing a 12-week university-based resistance training protocol with two distinct periodization
models in young university students. Retention, adherence, intervention fidelity, and data completeness
were high across groups, and no serious adverse events were observed. These findings indicate that
pág. 4575
supervised linear and undulating resistance training programs can be implemented in a university setting
with acceptable methodological control and participant engagement.
Both resistance training groups showed favorable preliminary changes in executive function outcomes,
physical performance, body composition, and selected peripheral biomarkers when compared with the
active control condition. Improvements were observed in inhibitory control, working memory, cognitive
flexibility, estimated maximal strength, handgrip strength, countermovement jump, muscle mass, and
body fat percentage. The peripheral biomarker profile also showed favorable exploratory changes in
BDNF, cathepsin B, IGF-1, IL-6, and C-reactive protein. However, these biomarker findings must be
interpreted as peripheral systemic signals and not as direct evidence of central neuroplasticity,
neurogenesis, or causal brain-level adaptation.
The comparison between linear and undulating periodization suggested that both models are viable and
capable of producing preliminary adaptive responses. The undulating model showed numerically larger
changes in several executive, neuromuscular, morphological, and biomarker outcomes, whereas the
linear model showed a slightly stronger response in handgrip strength. This pattern does not justify a
definitive superiority claim. Instead, it suggests that future trials should examine whether the temporal
organization of resistance training load influences specific outcome domains when total exposure,
supervision, and adherence are adequately controlled.
Exploratory association analyses indicated that changes in strength, body composition, internal load,
and peripheral biomarkers were associated with changes in executive function in bivariate models.
Nevertheless, most associations were attenuated after adjustment for group, age, and sex. This finding
reinforces the need for mechanistic caution. The observed cognitive and biomarker changes should be
interpreted as preliminary signals linked to intervention exposure, not as evidence that any single
physiological marker mediated executive function improvement.
Overall, the study provides a coherent pilot foundation for a future definitive randomized controlled
trial. The next phase should include a larger sample size, preregistered primary cognitive endpoints,
stricter control of sleep, stress, diet, caffeine, and external physical activity, improved expectancy
monitoring, and standardized preanalytical procedures for biomarker collection. If feasible, future
studies should incorporate complementary neurophysiological or neuroimaging measures to test
supervised linear and undulating resistance training programs can be implemented in a university setting
with acceptable methodological control and participant engagement.
Both resistance training groups showed favorable preliminary changes in executive function outcomes,
physical performance, body composition, and selected peripheral biomarkers when compared with the
active control condition. Improvements were observed in inhibitory control, working memory, cognitive
flexibility, estimated maximal strength, handgrip strength, countermovement jump, muscle mass, and
body fat percentage. The peripheral biomarker profile also showed favorable exploratory changes in
BDNF, cathepsin B, IGF-1, IL-6, and C-reactive protein. However, these biomarker findings must be
interpreted as peripheral systemic signals and not as direct evidence of central neuroplasticity,
neurogenesis, or causal brain-level adaptation.
The comparison between linear and undulating periodization suggested that both models are viable and
capable of producing preliminary adaptive responses. The undulating model showed numerically larger
changes in several executive, neuromuscular, morphological, and biomarker outcomes, whereas the
linear model showed a slightly stronger response in handgrip strength. This pattern does not justify a
definitive superiority claim. Instead, it suggests that future trials should examine whether the temporal
organization of resistance training load influences specific outcome domains when total exposure,
supervision, and adherence are adequately controlled.
Exploratory association analyses indicated that changes in strength, body composition, internal load,
and peripheral biomarkers were associated with changes in executive function in bivariate models.
Nevertheless, most associations were attenuated after adjustment for group, age, and sex. This finding
reinforces the need for mechanistic caution. The observed cognitive and biomarker changes should be
interpreted as preliminary signals linked to intervention exposure, not as evidence that any single
physiological marker mediated executive function improvement.
Overall, the study provides a coherent pilot foundation for a future definitive randomized controlled
trial. The next phase should include a larger sample size, preregistered primary cognitive endpoints,
stricter control of sleep, stress, diet, caffeine, and external physical activity, improved expectancy
monitoring, and standardized preanalytical procedures for biomarker collection. If feasible, future
studies should incorporate complementary neurophysiological or neuroimaging measures to test
pág. 4576
mechanistic pathways more directly. Until then, the present findings should be understood as evidence
of feasibility and promising preliminary multidomain adaptation rather than confirmatory evidence of
efficacy or central neurobiological causation.
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