A COMPARISON OF EXERCISE SELECTION MANIPIULATION VERSUS
INTENSITY AND LOAD MANIPULATION ON IN-SEASON COLLEGIATE TRACK
AND FIELD ATHLETES

By

Jonathan W. Hummel, B.S.
East Stroudsburg University of Pennsylvania

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Exercise Science to the office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania

August 9, 2019

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ABSTRACT

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Exercise Science to the office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania.
Student Name: Jonathan W. Hummel
Title: A Comparison of Exercise Selection Manipulation Versus Intensity and Load
Manipulation on In-Season Collegiate Track and Field Athletes
Date of Graduation: August 9, 2019
Thesis Chair: Gavin Moir, Ph.D.
Thesis Member: Matthew Miltenberger, Ph.D.
Thesis Member: Shawn Munford, Ph.D.

Abstract
Introduction: The importance of periodization variables in research for athletic
populations is drastically overlooked. Proper periodization can allow for maximizing
athletic performance as well as reduction of common injuries found in sport. Purpose:
The purpose of this research is to compare the effects of exercise selection variation
versus exercise load and intensity variation on absolute strength and power measures
across a 4-week training block for in-season collegiate athletes. Methods: 14 Subjects
both male and female on a division 2 collegiate track and field team participated in 4
weeks of exercise sessions with two groups being one where exercise load and intensity
were used as a variable versus exercise selection being used as a variable of
programming. Absolute strength measures were used by measuring a 1RM back squat
using the GymAware device and power using a vertical jump, jump mat. Results: Results
indicate that no significance was found between the change in vertical jump or back squat
1RM from pre-post of either group (p>.05). Informal statistics had shown slight
improvements in means from the exercise load and intensity group but when numbers
were made relative to the subject improvement, the exercise selection group had
improved more. Discussion: The results lend to the idea that a block greater than 4 weeks
may be needed in order to elicit training adaptations favorable to the outcome of one
group over the other. In addition, both groups had improved which may also lend to the
idea that variation in general is necessary and it does not matter which type of variation.
Conclusion: In conclusion, no definitive method of introducing variation was found
favorable over another in the research.

TABLE OF CONTENTS
List of Figures…………………………………………………………………………………...vi
List of Tables…………………………………………………………………………………...vii
CHAPTER
I.

INTRODUCTION…………………………………………………………………….1
Background………………………………………………………………………………..1
Purpose………………………………………………………………………………….....5
Null Hypothesis………………………………………………………………………..….6

II.

LITERATURE REVIEW……………………………………………………………..7

III.

METHODOLOGY…………………………………………………………………..15

IV.

RESULTS……………………………………………………………………………20

V.

DISCUSSION……………………………………………………………………….28
Future Research………………………………………………………………………….31
Limitations……………………………………………………………………………….32
Delimitations……………………………………………………………………………..32

VI.

CONCLUSION……………………………………………………………………...34

APPENDICES……………………………………………………….…………………….…35
Appendix A IRB Form…………………………………………………………………...35
Appendix B Informed Consent Form……………………………………………………36
Appendix C PAR-Q+ Form…………………………………………………………...…39

iv

Appendix D 7-Criteria Wellness Questionnaire…………………………………………40
REFERENCES……………………………………………………………….………………41

v

LIST OF FIGURES
Figure
i.

Figure 1. Average Fatigue……...……...…………………………………………22

ii.

Figure 2. Average Power.……………………………………………………..…22

iii.

Figure 3. Average Well-being…………………………………...……………….23

iv.

Figure 4. Average Vertical Jump……………………………...…………………23

v.

Figure 5. Vertical Jump Independent-Samples Mann-Whitney U Test…….……26

vi.

Figure 6. 1RM Back Squat Independent-Samples Mann-Whitney U Test……....27

vi

LIST OF TABLES
Table
i.

Table 1. Weekly Wellness Delta………………………………...……………….20

ii.

Table 2. Delta Vertical Jump………………………………………………….....21

iii.

Table 3. Delta 1RM Squat……………………………………………………….24

iv.

Table 4. Smallest Worthwhile Change…………………………………………..25

v.

Table 5. Pre-Post Delta………………………………………………………..…25

vii

CHAPTER 1
INTRODUCTION

Background
Maximizing athletic performance is a multi-faceted process where practitioners
must be up to par with the latest methods to do so. In order to achieve this task, research
must be incorporated into the practical setting and applied in a manner that allows the
practitioner to maximize the athlete’s ability to perform. In strength and conditioning,
literature and other research lay the groundwork in order to program for athletes of
almost any sport or for any competition. Research in this area is important in order to
optimize athletic performance and to ensure athletes are getting the best opportunity for
growth. One of the biggest issues with strength and conditioning research in regards to
programming stems from the conflicting results of various different studies. In a study
done by Painter and researchers comparing undulating versus block periodization for
track and field athletes had shown that in this instance block styles of training had shown
similar statistic strength gains, but had a greater efficiency in providing strength gains
when looking at overall load between both programs (Painter et. Al., 2012). Various
other studies demonstrate similar results, but yet others exist demonstrating very
contrasting results. A second study done by Bartolomei also comparing an undulating
1

style of programming versus a block periodization style of exercise programming had
found contrasting results. Results in this study had shown that the undulating style of
programming used had actually been more advantageous over block periodization in
providing maximal strength measures (Bartolomei, 2015). Although these are two
isolated results, a deeper look into research shows similar findings. All different methods
of exercise programming have shown supportive results, research also has not given
further insight to whether one method of programming may be more advantageous than
another.
One of the most popular approaches to programming is periodization.
Periodization itself is built around the concept of the General Adaptation Syndrome
(GAS) presented by a researcher named Hans Selye. GAS generally states that the body
will adapt to a stressor that is presented to it, and thus will undergo favorable adaptation
to allow it to overcome this stressor (Selye, 1950). Periodization uses this concept to
present systematic “stressors” or in this case systematic variation to cause adaptation.
These elicited adaptations should be implemented in a sense that is also favorable to
increasing the athlete’s performance. Periodization is constructed in several different
forms, whether it be linear or undulating that can allow for variation in training intensity
and training volume. Linear periodization is a great start to build upon when considering
exercise programming, but falls short in various different stipulations. One of the major
components when considering linear periodization is peaking for a major competition.
This may be great for a sport where there are one or two major competitions but falls
short in sports where there are multiple major competitions throughout the season. A
second short-coming of periodization is the vague guidelines on adding exercise

2

variation. Going back to the idea of GAS, variation must be introduced in order to
provide a stressor the body can overcome and thus adapt to. The main stressors in which
periodization focuses on are exercise intensity, frequency, and load. These stressors are
typically introduced and manipulated across cycles of 4-6 weeks to cause adaptation.
When exploring the possibilities of variation, one factor that is mentioned but given little
to no guidelines or explanations to be implemented is exercise variation in comparison to
volume-load. Specific exercise variations have been suggested to drive adaptations within
training blocks, but exercise selection has not been isolated as its own individual factor.
Even looking at the previously mentioned study done by Painter and researchers, it’s seen
that within the block periodization group, exercise selection and volume load are both
being manipulated. Since both factors are manipulated simultaneously, this also means
you cannot infer adaptation from either aforementioned variable. Exercise variation as a
sole variable is vastly overlooked and under-researched, but can theoretically provide
major performance advantages. A typical goal of the introduction of variation is to avoid
a plateau of improvement, and avoid injury. By systematically introducing exercise
variation in a timely manner both of these goals can be met while still making
progressive gains in strength throughout a workout cycle. In a theoretical exercise
program, mesocycle 1 may involve a normal back squat with emphasis on strength.
Mesocycle 2 may involve a variation of the back squat such as a pin squat again with an
emphasis on strength. Both mesocycles are still working on the athlete’s lower body
strength, but by manipulating the variation of the focus exercise, the athlete is able to
continue to work lower body strength. In this theoretical example, the athlete is able to
change muscle recruitment as well as range of motion throughout the exercise as a means

3

of variation. By changing the range of motion being used, the athlete may be able to
avoid over-use injury as well. A secondary benefit to exercise variation manipulation is to
prepare the athlete for dynamic situations that arise during sport. An athlete will face
various ranges of motion throughout a competition, and hence by placing the athlete in
different movement patterns in training, they will be better prepared for competition.
In order to investigate exercise variation as a gap in the literature, a primary step
would be to compare two exercise programs across 4 weeks in which one has
manipulation through exercise intensity and volume but exercise selection is held
relatively constant, versus having a second program where exercise and volume are
equated to equal to the first group but will in turn have manipulation through exercise
selection. In order to equate exercise intensity and volume of each group, the intensities
will be added together and averaged from each week of program 1 where the exercise is
held constant. The average intensity from program 1 will then be the intensity for
program 2 in which the exercise selection is manipulated weekly. Overall workout
volume will not be equated due to making the results applicable to a practical setting
where workout volume is different amongst different programs. Subjects will be selected
from the track and field athletes at East Stroudsburg University and participate in
throwing events. To make the research successful, multiple measures of assessment must
be utilized through a monitoring program. The focus of the study is on power and
maximal strength making the utilization of the GymAware unit necessary, and will
provide manageable methods of obtaining both measures of 1-RM strength and force
velocity characteristics in one singular test. A secondary measure of power will be the
utilization of the Just Jump Mat with the digital timer. First of all, by testing vertical

4

jump, the practitioner can get an efficient and simple measure of explosive power. In
addition, measuring vertical jump prior to exercise may give insight to fatigue of the
subject. It is known that as an individual becomes fatigued, their vertical jump
performance will also decline (Smilios, 1998). If vertical jump assessment is done
properly and timely throughout the entire program it may also give an insight to the
fatigue the subject experiences prior to initiating each workout. This can be done by
comparing the pre-testing vertical jump value to the pre-exercise measure vertical jump
value. Vertical jump measures across multiple days can also be compared to see if a
specific workout causes more fatigue than another. Gathercole and researchers had
previously demonstrated that the utilization of a countermovement jump was not only an
efficient method of measuring fatigue, but also repeatable and comparable across
multiple days (Gathercole, 2015). By assessing fatigue, the researcher may be able to use
this information in order of a measure of prediction of future performance too. In
additional to daily measures of power and fatigue, other measures such as a sleep
questionnaire, wellness questionnaire, and food and activity logs will be used in order to
account for any external factors that may impact performance.
Purpose
To compare the effects of exercise selection variation versus exercise load and
intensity variation on absolute strength and power measures across a 4-week training
block for in-season collegiate athletes.

5

Null Hypothesis
There will be no difference between either exercise selection variation groups
versus exercise load and intensity variation groups on absolute strength and power
measures across the 4-week training block for in-season collegiate athletes.
There will also be no difference between either group in regards to power output
measured through vertical jump.
There will be no difference between either group in regards to maximal strength
characteristics measured through a 1 repetition maximum back squat.

6

CHAPTER 2
LITERATURE REVIEW
In the current chapter, existing literature will be reviewed pertaining to the purpose of
this study. In order to understand the rationale of comparing intensity versus exercise

selection as variables of programming, it is important to first gather background on the
process of adaptation and why these factors matter. Adaptation is the process of which an
organism gains a new functional capacity from repeat exposure to a stressor. A stressor
on the other hand is something that perturbates the organism further from a homeostatic
state – causing stress to the system. In the most basic sense, the idea of adaptation from a
stressor in relation to human physiology originally stemmed from a researcher named
Hans Selye, who coined the process known as the General Adaptation Syndrome or GAS.
In Selye’s research, it is mentioned that any organism can respond to stress, and
overcome this stressor through adapting to it. This process occurs regardless of the
stressor that is being presented and may even take place over generations of living
organisms in order to evolve to adapt to whatever stressor is consistently present. Selye
continues this discussion in stating that the adaptation process occurs through multiple
phases. The first phase of which is the “Alarm Reaction” phase, followed by the
“Resistance” phase, and finally the “Exhaustion” stage (Selye, 1950). Essentially, the
7

stressor is presented and the body will attempt to resist the stressor in an attempt to
maintain equilibrium and in which case adaptation will occur. This process also occurs
with exercise and the positive adaptation can vary depending on what mode or variables
are present throughout. In the case of this study, two variables to consider as stressors is
the variation of the exercise given or the intensity and load of the exercise give.
Looking past the general sense of adaptation, this process can and does occur with
exercise. Referring back to GAS, when someone exercises, they are simply exposing
themselves to a stressor whether it is external resistance (weight training) or aerobic
stresses (endurance training). With weight training, the individual imposes an external
resistance to their body which acts as a stressor. By consistently exposing the body to this
external resistance, the body will adapt and overcome the stressor presented through
adaptation. These adaptations to resistance training are well documented and can take
place in the form of both neural and muscular adaptations. Some of the accepted neural
changes that are supported through research are motor unit synchronization and rate
coding. Synchronization is the ability to recruit a greater number of motor units with a
decreased latency period, meaning they can respond quicker to a stimulus by producing
force more rapidly. Additionally, after adaptation takes place, these motor units can fire
in conjunction with one another. This would infer that with more muscle fibers being
active at a given contraction, the force production would also be increased. A study done
by Semmler at the University of Colorado Boulder had highlighted some key points
regarding motor unit synchronization and neuromuscular performance. In this study, one
consistent finding was that multiple supporting evidence has shown following physical
activity and even more specifically strength training causes increases in motor unit

8

synchronization (Semmler, 2002). In fact, results showing increases of motor unit
synchronization occurring as a product of strength training have been documented for a
while now. A second study done in 1975 that had also investigated motor unit
synchronization had found that following a 6-week strength training program, motor unit
synchronization had also been theorized to have increased (Milner-Brown, 1975). Just as
motor unit synchronization is well documented, so is rate coding. Rate coding is the rate
at which a neural impulse is conducted to the individual motor units that comprise the
muscle. Of course, this is also an adaptation that takes place following resistance training
or explosive training such as plyometrics or short sprints. One of the earlier studies done
in 1978 by Desmedt and Godaux had looked at the properties contraction rate can play
with force production by investigating the discharge patterns of singular motor units. In
this study, the researchers compared a voluntary ballistic contraction to a slow ramping
voluntary contraction. Contractions were compared in several different fibers from the
masseter, soleus, and the first dorsal interosseous muscles. Results had indicated that the
force produced during the ramp conditions were actually greater than those produced
through ballistic conditions (Desmedt, 1978). Although this doesn’t directly lead to the
determination of rate coding, it does tell us that the rate at which the muscle contraction
takes place does share a correlation to the force being produced. A second study done by
Harvard University’s medical school had used fibers from a soleus of a cat to
demonstrate different muscle fiber characteristics. The researchers had highlighted the
relationship of the conduction velocity and maximal force production of the fibers
examined. It was found that there is an apparent relationship between the maximum
tension of the motor unit and the conduction velocity of its axon. This relationship

9

demonstrated that slowly conducting fibers supplied the smaller motor units where-as the
rapidly conducting fibers supplied the larger motor units (McPhedran, 1965). These
studies help to highlight the importance that rate coding can make on force production,
and show that the rate of the muscular contraction can play a direct role in the force being
produced by the muscle.
Keeping in mind that the stressor presented is simply an increased external
resistance, these neural adaptations allow for greater force production which eventually
leads to overcoming the stress of the external resistance. Aside from the aforementioned
neural adaptations, stressing the muscular system can elicit muscular adaptations too. The
main muscular adaptation is called muscular hypertrophy. Muscular hypertrophy is the
increase of the muscle size through an increase in the muscular cross-sectional area.
Muscular hypertrophy has extensive research backing it’s increase in force production
capabilities (Goldberg, 1975). Studies across multiple populations of subjects have even
found increases in hypertrophy as well as maximal strength following strength training
protocols. A study done by researched in 1991 had shown that following a 12-week
resistance training protocol for elderly women, muscular cross-sectional area had
increased by an average of 20% in type 2 fibers and maximal strength characteristics had
increased by an average range of 28-115% in comparison to baseline measures (Charette,
1991). Backed by research of countless studies, it’s evident that muscular hypertrophy is
also well documented as an adaptation to strength training.
Although viewing resistance training as a stressor to the organism presents
multiple adaptations, there are numerous studies proving endurance training elicits
adaptations too. Some of the widely accepted adaptations that can take place through
10

endurance training are an increase in VO2 max, increased mitochondrial density,
increased cardiac output through increases in stroke volume, increase left ventricular
volume and end diastolic volume, along with multiple other cellular adaptations. Just as
with resistance training, taxing the cardiovascular system also presents a stressor to the
organism in which the adaptation process can take place. Some studies demonstrate
adaptations to cardiovascular training in as little as 10 days. A study done by Mier and
other researchers had looked at cardiovascular adaptations following 10 days of a cycle
protocol. Throughout the 10 days of the study, subjects had completed multiple cycling
training sessions at various intensities correlated to a pre-tested VO2 peak. At the end of
the study, the researchers had found that consistent endurance training had caused an
increase in plasma volume, and increases in cardiac output and stroke volume during
peak exercise (Mier, 1997). Although this study was only 10 days in duration, it still had
shown cardiovascular adaptations taking place in such a short duration.
When looking to elicit an adaptation, several over-arching variables become
evident. The key variables in any program should be overload, specificity, and variation.
It’s clear that adaptation takes place in both aerobic and muscular capacities, but how you
elicit these adaptations is what becomes key. As the body adapts to the stressor, it
becomes necessary to further increase the stress placed upon the system in order to
continue adaptation. The principle of overload when referring to training simply means
that as the body adapts to the stress placed upon it, it must then be stressed to a greater
means than previously done in order to continue positive adaptation. When planning an
exercise program, causing stress to the system can be tricky. An exercise program which
stresses the system too much may cause exhaustion, and negative adaptation leading to

11

overtraining or burnout. An effective exercise program will allow enough stress for
positive adaptation, but not too much stress and thus avoiding exhaustion. Typically, a
gradual increase in the load being used in weight training or the intensity of aerobic is a
standard means of ensuring overload. This leads into the next variable of exercise
programming which is specificity. Specificity is ensuring that the adaptation is going to
be advantageous for the desired outcome (Specificity – Science and Practice). A simple
example is that if you are aiming to increase strength, it would not be specific nor
advantageous to perform endurance training. If you are planning a program to increase
strength, focus on the specific variable of strength to cause the desired outcome. A final
variable which is key to this study specifically is the idea of variation. Variation in
training is simply varying the load or intensity of the exercise being performed. This can
be a method of creating overload, but also can be looked at as training for a specific
outcome. In a traditional sense, variation when mentioned in research is typically in the
form of changing the exercise load or exercise intensity (Zatsiorsky, 2006). Another
variable which plays a major role in variation is varying exercise selection. Exercise
selection has been mentioned but no major research has been done on whether or whether
not it is advantageous or not. Part of the research in this study is to investigate its
effectiveness when viewed as a method of variation in compared to traditional methods
such as load and intensity.
Overlooking the entire process of adaptation and the factors eliciting them is the
planning and implementation of the stressor in order to produce the desired adaptation. A
method commonly used to present stressors to create adaptation is a form of
programming called periodization. Periodization is the systematic programming of

12

exercise variables in order to create a desired adaptation. These key exercise variables are
those just mentioned such as overload, specificity, and variation. Periodization can be
done for both aerobic and strength training, but should be tailored around the goals of the
athlete or client. For example, a periodization program focusing on increasing muscular
strength is going to be drastically different than a program looking to improve endurance.
When planning periodization, several methods of combining the key exercise variables
mentioned exist. Two of the main styles of periodization are undulating periodization and
block periodization. Undulating periodization can take place in several different ways
such as weekly or even daily undulations. In undulating periodization, training weeks or
training days contain variations of exercise intensity and load and in some cases exercise
variation depending on the style. A great example of undulating periodization showing
increases in strength output was done by Bartolmei and other researchers in 2015. In this
study, weekly undulating periodization was used in which case a 10-week training
protocol was used and subjects trained 3 times a week. Results of this study had shown
that weekly undulating periodization had shown improvements over block periodization
when looking at lower body strength and power measures (Bartolomei, 2015). Although
this study had focused on undulating periodization, many other studies focus on another
form of periodization called block periodization. In block periodization, training is
organized into blocks where a specific focus in placed on the desired outcome. For
example, a training block may look like 4-6 weeks of 85% intensity and 4-6 repetitions in
a desired exercise to focus on maximal strength as the desired outcome. A second study
done comparing block and undulating styles of periodization had contrasting results and
had actually shown block periodization to be advantageous over undulating. Painter,

13

Haff, and other researchers at Edith Cowen University had investigated block vs
undulating style of periodization. In this study, block periodization group had performed
exercises 3x a week for 10 weeks total. This 10-week period consisted of two 4-week
blocks as well as one 2-week block at the end prior to post testing. Each block consisted
of an individual focus, so block 1 was strength/endurance, block 2 was strength, and
block 2 was power. Results had indicated that the block periodization had an advantage
over undulating style of periodization in the form of efficiency of strength gains (Painter,
2012). Although both studies show contrasting results in regards to which style of
periodization may be more effective, the common ground they share is that their main
source of variation throughout the study is a variation in the load and intensity. Neither of
these studies, regardless of the form of periodization, focus on varying the exercise
selection as a method of variation. An effective method of determining the different
exercise selection could make in comparison to load and intensity would be to compare
the two variables to determine whether or whether not exercise selection can be a valid
factor of variation. Therefore, the purpose of this study is to compare the effects of
exercise load and intensity variation versus exercise selection variation on absolute
strength and power measures across a 4-week training block for in-season collegiate
athletes. An additional question that is pertinent is which method of variation will have a
greater impact on performance to the athlete.

14

CHAPTER 3
METHODOLOGY
In the chapter 3, the methodology of the research will be outlined. The very first
step of the methodology was to determine the proper subject pool for the research. The
best subjects for the experiment were found to be power and strength-based athletes
based on the performance outcomes being measured. The primary performance measures
entail testing maximal strength via GymAware Unit which allowed the testing of force
velocity characteristics at both the pre and post experiment time as well. Secondary
measures included a pre-session vertical jump as well as a pre-session 7 criteria wellness
assessment. Both of these measures provided as a secondary measure for power and
fatigue across workouts. Subjects were both male and female for the experiment (n=14).
In this case, all subjects were college aged male and female division 2 track and field
athletes. One of the secondary criteria to be selected is that the athletes primary event had
to be power based, this included jumps, throws, and short sprints events. At the start of
the study, Group 1 had a total of 3 throwing athletes, 2 multi-event athletes, and 3 sprintbased athletes (group 1; n=8). Group 2 had a total of 3 throwing based athletes, 2 multievent athletes, and 3 sprint-based athletes (group 2; n=8). Additionally, group 1 had a
total of 6 male athletes and 2 female athletes. Group 2 had a total of 5 male athletes and 3
15

female athletes. At the end of the study, 2 subjects had been dropped from group 2 (both
sprint-based athletes) due to un-related injury that had occurred outside of track and field
and research related grounds. In addition, all subjects had been exposed to and performed
linear periodization prior to the initiation of the current research study.
One of the first procedural steps to the research involved informing the subjects
of the risks & rewards of participating in the study. This also included informing the
subjects of the methodology and what they will be participating in. Once the subjects
were informed of what was proposed, they were asked to fill out an informed consent
form, as well as PAR-Q assessments to determine whether or whether not they were fit
for physical activity. After the subjects were informed, and the initial precautions are
taken, the subjects were randomly selected and randomly assigned to one of two groups.
An attempt to balance groups based on gender and event was made in order to equalize
groups by splitting gender and track events, and taken a step further by randomly and
equally assigning subjects to either group 1 or group 2. Group 1 focused on weekly
manipulations of exercise intensity and load with exercise selection held constant i.e.
performing back squat for a total of 4 weeks. Group 2 focused on weekly manipulations
of exercise selection with exercise intensity and load held constant for a total of 4 weeks.
In order to equate for intensities and workloads being different, the average of all of the
intensities of group 1 was used as the average for group 2. Exercise intensities were
averaged across both groups due to eliminating any extrigent factors. Total load
throughout the week was not averaged in order to keep the results applicable to a
practical setting. For example, if group 1 has quarter squats as a variation of the back
squat, in a practical setting the load will not be reduced to be equated to a normal back

16

squat. The exercise program itself consisted of back squat with manipulations in load and
intensity for group 1, and variations of back squat for group 2. Exercises outside of the
scope of the study were held constant across both groups. This included total volume at
track and field practices, as well as any additional conditioning and weight training was
attempted to be made equal within event groups. The exercises were performed 2 days a
week with 48 hours rest between exercise days for 4 weeks in duration. The loads and
intensities were recorded every session, as well as various other measurements such as
the jump mat vertical jump test, and 7-criteria wellness questionnaire. Once assigned to
either group 1 or group 2, the subjects then underwent familiarization and pre-testing the
week prior to initiation of the 4-week program. On this pre-testing day the subjects
performed familiarization trials and 3 vertical jump trials on the jump mat, as well as
familiarization and max testing with the back squat using the GymAware Unit to assess
max strength and force velocity characteristics. Maximal strength using the GymAware
unit was assessed using the two-point method (García-Ramos, 2018). At pre-testing,
subjects also were instructed on the usage of the 7-criteria wellness questionnaire.
Initiation of the wellness questionnaire started the week prior to the initiation of the
exercise protocol in order to get a better assessment of the subject’s well-being before the
program even started. In week 2, the exercise program began for both groups of the
experiment. Subjects from both groups engaged in 3 vertical jump trials where the best
number was recorded. This was be done in order to assess fatigue throughout the
program. Additionally, this also allowed insight to which day or which exercise variation
could have caused the greatest fatigue to the subject. Group 1 started with a normal back
squat at the desired percentage and load for week 1. Every week, the intensity and load

17

were manipulated but the exercise remained the same. Group 2 started with the average
intensity of all 4 weeks from group 1, but had a different exercise variation i.e. box squat.
Every week the variation of the back squat was manipulated in group 2 keeping intensity
at the average of group 1’s. The desired exercise intensity was manipulated based off the
exercise variation for group 2. In addition, the GymAware unit was used in order to make
adjustments based off velocity and using Bryan Mann’s velocity ranges as a reference for
the correct intensity. The actual load was not reduced to match between both groups in
order to ensure the practicality of the study. For example, if a quarter squat is being
utilized, the load would be far greater than a normal back squat. This would be additional
load of the quarter squat would be key in adaptation in a practical setting, so for the
purpose of this research the loads were not equated between both groups. Prior to each
session, each week the subjects completed and turned in a wellness questionnaire as well
as completed their 3 trials of vertical jump. After each session, the subject’s load,
intensity, repetitions, and any additional notes regarding the exercise performance was
taken to get the best assessment. Post 4 weeks of training, 2 sessions per week, 8 total
sessions the subjects performed post-testing assessments. During the exercise sessions, 2
subjects had dropped from the study due to unrelated reasons and both subjects were
from group 2. On the week following the exercise program, the remaining subjects
completed the 7-criteria wellness assessment, as well as the same testing as pre-testing
where they performed vertical jump testing on the jump mat, and again GymAware unit
was used to detect any changes in force-velocity characteristics and maximal strength for
their back squat. All sessions within the study were supervised by a NSCA certified
college strength and condition coach in order to ensure proper form, proper load, and

18

completion of the workout and procedures given. Equal encouragement and similar
instruction were given across all subjects of both groups. At the completion of data
collection, pre-testing was compared to post-testing, and the statistically significant of
any reported changes was be analyzed. For formal statistics, a Mann-Whitney U test was
used as a measure of nonparametric statistical analysis to account for the uneven
distribution of subject numbers across the groups.

19

CHAPTER 4
RESULTS
Table 1. Weekly Wellness Data

Table 1 shows the change in fatigue compared both groups. A red value indicates
that group 1 had a lower value than group 2. Group 1 had scored lower (better) than
group 2 on Fatigue, General Muscle, Pain/Stiffness, and Stress. Group 2 had scored better
on Power, Sleep Quality, and Well-Being.

20

Table 2. Delta Vertical Jump

Table 2 depicts the descriptive characteristics of the change in vertical jump for
both groups from pre-post testing. The mean and overall relative mean only include pre
and post testing values. Overall values include any trial that had taken place across the
entire study. Relative values were the average change in vertical jump equated to the
number of subjects in each group.

21

Figure 1. Average Fatigue
Figure 1 depicts a comparison of fatigue between both groups. The illustrated points are
the averages across the 4 weeks of the study. The lower the value, the less fatigued the
subjects are reporting.

Figure 2. Average Power

22

Figure 2 depicts the average rating of power between both groups across the 4 weeks.
The lower the value means the more powerful the subject is reporting.

Figure 3. Average Well-Being
Figure 3 depicts a comparison the average rating of well-being across both groups. The
lower the value means the better overall the subject is reporting.

Figure 4. Average Vertical Jump.

23

Figure 4 depicts the average of all 4 weeks of the vertical jump trials taken from both
groups.

Table 3. Delta 1RM Squat

Table 3 includes the change in 1-RM back squat in each group from pre-post testing.
Relative values were the average change in 1-RM equated to the number of subjects in
each group.

24

Table 4. Smallest Worthwhile Change
Table 4
Smallest Worthwhile Change
Standard Deviation
Smallest Worthwhile Change
1-RM (lbs)
84.464
16.8928
Vertical Jump (in.)
4.409
0.8818
Note. 1-RM was performed with the backsquat exercise.

Table 4 includes the standard deviation across all subjects as well as the smallest
worthwhile change in all subjects across both 1-RM and Vertical Jump.

Table 5. Pre-Post Data
Table 5
Pre-Post Delta
Group 1
Subject 1
Subject 2
Subject 3
Subject 4
Subject 5
Subject 6
Subject 7
Subject 8
AVERAGE
Relatives

VJ
0.8
0.7
3.6
0.2
3
0.7
0.3
0.2
1.19
0.15

Measured Max
22.0
3.0
5.0
-6.1
15.2
20.4
0.3
2.3
7.76
0.97

Group 2
Subject 9
Subject 10
Subject 11
Subject 12
Subject 13
Subject 14
Subject 15
Subject 16
AVERAGE
Relatives

VJ

Measured Max

1.3
0.1
2.6
-3.8
1.7
1.8

15.3
1.5
21.0
-38.7
24.7
17.1

0.62
0.10

6.79
1.13

*Note. A highlighted value indicates improvement past the smallest worthwhile change. A yellow highlight indicates subject dropout. A red color font indicates subjects who did not improve or had gotten worse.

Table 5 depicts all of the subject’s delta scores from pre-post and illustrates
improvement, decrement, and attainment of the smallest worthwhile change.

25

Figure 5. Vertical Jump Independent-Samples Mann-Whitney U Test

Figure 5 demonstrates the spread and significance of the change in vertical jump
from pre-post testing for both groups as determined by the Mann Whitney-U test. The
result was found to be insignificant with a P value of 1.0 (p>.05).

26

Figure 6. 1RM Back Squat Independent-Samples Mann-Whitney U Test

Figure 6 demonstrates the spread and significance of the change in squat from
pre-post testing for both groups as determined by the Mann Whitney-U test. The result
was found to be insignificant with a P value of .573 (p>.05).

27

CHAPTER 5
DISCUSSION
In chapter 5, the results will be discussed. Looking at the results, it was found that
neither group had presented any statistically significant changes despite looking at both
the change in vertical jump and back squat 1RM across both groups. Although no
statistical significance was found, looking at the raw data and informal descriptive, some
slight advantages were found across groups. In looking at the ratings received from the
questionnaire, it appeared that group 1 (Exercise Load Manipulations) had performed
better in Fatigue, Pain/Stiffness, General Muscle Strain, and Stress measures. In contrast,
group 2 (Exercise Selection Manipulations) had actually performed better in Power,
Sleep Quality, and Overall Well-Being. Although group 1 had performed slightly better
in more measures than group 2, it could be argued that the measures group 2 performed
better in were actually more pertinent to the success of the athlete. Keeping the ratings of
wellness in mind, the results had shown interesting findings when looking at the change
in vertical jump throughout the study. Comparing Figures 1-4, it’s interesting to note that
group 2 appears to have better ratings of overall well-being and power but higher
measures in fatigue. This illustrates that although group 2 reported being more fatigued
than group 1, they had also reported feeling more powerful and overall better. Comparing
28

the wellness figures to the vertical jump figure, week 3 seems to show that when the
athletes reported lower (better) scores in power and fatigue, they had actually
experienced a decrement in vertical jump performance. Contrary to what would be
expected, feeling more powerful and less fatigued would be expected that a higher
average vertical jump would be seen across the subjects of group 2. A final note looking
at the tables is simply examining figure 1 showing fatigue. It appears that group 2 has a
slightly higher fluctuation of measure of fatigue which can indicate that the alternating
exercise selection may be causing additional fatigue in comparison to group 1 who is
performing the same exercise and may be exposed to less stimulus. Table 2 depicts the
changes in vertical jump throughout the study and also looking at pre-post measures too.
When taking the average change in vertical jump for both groups in the pre-post testing,
group 1 has a slight advantage with a change of 1.1875 compared to the lesser
improvement in group 2 of .6167. Group 1 also had a similar advantage over group 2
when these means were made relative to the subject number. Since subjects performed a
vertical jump trial every exercise session, the overall means (all jump trials throughout
the study included) and relative overall means were also used in a comparison. When
looking at every vertical jump taken throughout the study, group 2 ended up having a
slight advantage and had greater improvement than group 1. This may suggest a few
things; the first being that the subjects of group 2 accumulated a greater level of fatigue
throughout their 4 weeks of workouts and did worse during post testing. The second
indication could lead to the idea the 1 + ¼ squat variation performed in the last week may
have created excess fatigue for post testing as well. Group 2 also had a singular subject
that had performed worse beyond normal measures which can be found in the spread of

29

the Mann-Whitney U figures, and could have also affected the data in the pre-post
comparison. This trend may be completely different given a larger subject pool. Looking
at the change in squat from pre-post it is found that again group 1 has a slight advantage
looking at the mean change. When results were made relative to the subject discrepancy
across groups, group 2 actually ends up having a higher advantage per subject in squat
improvement when compared to group 1. Interestingly enough, when the measures were
made relative and the all of the vertical jump trials across the entire study were used,
group 2 had slightly better improvements per subject. When the measures were kept prepost, and improvements were looked at the group rather than made relative to the subject,
group 1 had slightly better improvements. Regardless of improvement, the differences
found between groups was very slight and when formal statistics were run, they were also
found to be insignificant (p>.05). Finally, looking at table 4, the standard deviation of
pre-testing measures were taken as well as the smallest worthwhile change was calculated
through a 20% of the standard deviation. Using these values, looking at table 5 the total
improvement, attainment of the smallest worthwhile change, and even performance
decrement for both variables are illustrated. Group 1 had every subject improve in the
vertical jump but only 2 out of 8 subjects had attained the smallest worthwhile change. In
addition, only 2 out of 8 subjects attained the smallest worthwhile change in the back
squat 1-RM measurement as well. In group 1, all subjects had actually improved except
subject #4 in the 1-RM. In group 2, 4 subjects of 6 had achieved improvement further
than the smallest worthwhile change and all but one subject, subject #13, improved in the
vertical jump. In 1-RM measurement, all subjects but subject #13 had improved and 2 out
of 6 subjects had improved past the smallest worthwhile change. Looking again at the

30

smallest worthwhile change, it appears that subjects had actually improved slightly more
in group 2 than in group 1 when using the smallest change as a threshold of
improvement. One subject from group 2 had not improved and had actually post tested
worse, which can indicate the subject had been fatigued coming into the post-testing
session.
Future Research
An important note is that when looking at other research that involves matters of
periodization, it appears research is conducted across around 10-15 weeks in duration
(Painter, 2012; Bartolomei, 2015). In addition, these studies looked at 2-3 4-week blocks
of training rather than one singular block of training. Research is conducted in this
manner due to the time required to acquire a noticeable training adaptation. For future
research, it could be vital to incorporate a longer study duration and even increasing each
cycle of either intensity/load scheme or exercise selection scheme in order to create a
difference between exercise groups. Keeping in mind that improvements still occurred in
both groups, and ever so slight differences were also seen in both groups, it could be
reasonable to assume that the present differences would also be greater in the study
duration was longer as well. Given 8-12 weeks where multiple training blocks could take
place could separate the two groups from another and noticeable and significant changes
from pre-post could be evident. In addition, following traditional periodization, most
mesocycles are typically 2-4 weeks in duration, in which a specific scheme of intensity or
modes of exercise are used. Again, this is to allow favorable adaptation, but could also be
applied to this current research. A great start would be to allow 2-4 weeks per exercise
variation in order to also allow further adaptation.
31

Limitations
Some potential limitations that were evident in the research had to do with the
duration and subject size. In regards to duration, this was briefly mentioned above, but to
elaborate further is simply allowing time for adaptation to occur from training. Since this
study contained 4 weeks of training, and essentially 1 week per variation of load/intensity
or exercise variation this could limit the amount of adaptation that could have taken
place. By increasing the duration of study and possible extending the duration of each
cycle of variations to closer 2-4 weeks in length, further adaptation could take place and a
noticeable and significant trend in the differences between both groups could be more
evident.
Although the duration of the study was a potential limitation, the number of
subjects was a limitation as well. This research contained 14 subjects, but due to drop
outs in group 2, the groups were not equally distributed. This caused the means of the
improvements found in the study to favor the group which had the larger subject size. In
addition, the smaller subject size per group also had created any outliers to skew the
overall data more. For example, in looking at the formal statistics and the spread of the
data, one subject had lowered the means and spread of data drastically.
Delimitations
All subjects were required to be on the active division 2 collegiate track and field
roster, as well as had to have their primary track and field event be power based in nature.
This entailed throwing events, jumping events, short sprints (under 200m), and multievent athletes that had their primary event being a power event. As groups were

32

randomized, they were also randomly and equally balanced across both gender and event
group so an equal number of each gender and event group was found in both of the two
groups used in the study. All athletes were supervised by a certified strength and
conditioning coach at every testing session, and every exercise session to ensure proper
exercise form as well as adequate effort and completion of the program. A 7-criteria
wellness questionnaire was performed as well as 3 vertical jump trials at every session in
order to assess fatigue and allow for a constant monitoring throughout the study. Finally,
two weeks were chosen at random for a nutritional log to ensure the nutrition is relatively
similar across both groups as a final measure of attempting to eliminate any confounding
variables.

33

CHAPTER 6
CONCLUSION
In conclusion, although no statistical significance was found between exercise
groups both groups continued to improve. Exercise load and intensity variation group had
improved with means in every measure over the exercise variation group. Due to the
uneven subject distribution, relative measures were completed in which case the exercise
variation group had a greater improvement per subject in both power and strength
measures in comparison to exercise load and intensity variation group. Looking at
improvement using the smallest worthwhile change, group 2 had demonstrated a larger
number of subjects improving to this threshold in comparison to group 1 especially in the
vertical jump. Further research may lend to increasing the duration of the study as well as
increasing the subject size to make any noticeable adaptations more pronounced.

34

APPENDICES
APPENDIX A IRB FORM

35

APPENDIX B INFORMED CONSENT FORM
Informed consent for scientific study

Title of investigation: A Comparison of Exercise Selection Manipulation Versus Intensity
and Load Manipulation on In-Season Collegiate Track and Field Athletes.
Principle investigator: Jonathan Hummel
Overview of study
The desire to maximize athletic performance requires practitioners to be up to date with
the latest methods in order to do so. One of the greatest challenges for a practitioner is finding the
ideal method of exercise programming that best suites the athletic population that is being trained.
The most common approach in exercise programming involves a process called periodization,
where stressors are systematically introduced on the athlete in order to create variation in which
the body can adapt to and grow stronger from. Current research still relies on these methods by
focusing on the introduction of exercise intensity or exercise load variation in order to introduce a
stimulus to cause adaptation. As current research falls short in the congruity of its findings, it also
neglects guidelines of a vastly under-utilized method of variation such as varying exercise
selection.
The current aim of this study is to investigate exercise selection as an additional variable
to cause adaptation. Exercise selection in current research is only suggested in terms of specificity,
meaning more specific as a workout cycle ensues closer to competition periods. The proposed idea
is unique in the idea of examining varying exercise selection versus a group that follows a more
traditional route of varying solely exercise intensity and exercise load. Therefore, the purpose of
this study is to compare exercise selection manipulation versus intensity and load

manipulation on in-season collegiate track and field athletes.
Testing sessions
There will be 10 total sessions during the study and sessions will be performed in the Athletic
Weight room In Koehler Field of East Stroudsburg University. The sessions will be as follows:
Session 1: Pre-Testing
Session 1 will take place the first week of the initiation of the study. Participants will be
required to perform a standardized warm-up, a vertical jump trial, 1-RM using a linear position

36

transducer, as well as a postural balance assessment. At this period of time, exercise technique will
be assessed in addition to testing in order eliminate unnecessary risks of musculoskeletal injury.
Sessions 2-9: Exercise Programming
Following an adequate recovery of at least 3 days minimum, participants will begin
exercise programming sessions (2 per week) in their respective experimental groups.
Experimental group 1 will perform the back squat exercise using the current scheme:
-

Week 1: Back Squat at 85% | 3 x 5

-

Week 2: Back Squat at 87% | 3 x 4

-

Week 3: Back Squat at 90% | 3 x 2

-

Week 4: Back Squat at 85% | 3 x 5

Experimental Group 2 will perform the average intensity of group 1 (86.75%) but instead perform
a variation of the back squat using the current scheme:
-

Week 1: Pin Squat at 86.75% | 3 x 4

-

Week 2: Box Squat at 86.75% | 3 x 4

-

Week 3: Quarter Squat at 86.75% | 3 x 4

-

Week 4: 1 ¼ Squat at 86.75% | 3 x 4

Each experimental group will perform a total of 96 working repetitions, at an average intensity
of 86.75% with 5 minutes of rest between consecutive working sets. Participants will also be given
3 warm-up sets in order to work up to their desired percentage. A minimum of 3 days between
testing and exercise sessions, as well as 48 hours minimum between consecutive exercise session
will be given for recovery. Prior to the start of any physical activity for that day, participants will
also partake in a subjective monitoring program assessing both physical and psychological factors
that may impact performance. Physical measures include fatigue, general muscle, power,
pain/stiffness in which participants will rate these measures on a Likert scale of 1-5 (1 being “As
good as possible”; 5 being “As bad as possible”). Psychological measures include sleep quality,
stress, and well-being following the same 1-5 Likert rating scale. Additional measures of
monitoring will include a randomly selected food log for a week for both groups, as well as activity
logs for the day. Before exercise programming commences, both groups will go through a
standardized warm-up, at the end of the warm-up, participants will go through 3 measured vertical
jump trials in which the best trial will be taken. This will allow for a secondary measure of the
subject’s fatigue by comparing vertical jump heights across days.
Session 10: Post-Testing

37

Post-testing procedures will be held as similar to pre-testing as allowable. Participants will
be required to perform a standardized warm-up, a vertical jump trial, and a 1-RM using a linear
position transducer.
As a measure of precaution, the standardized warm-up, exercise technique assessment at
pre-testing, & subjective monitoring program will be used in order to reduce the likelihood of
musculoskeletal injury. In addition, spotters will be used during the back squat exercise to ensure
the participants safety at all sessions.
Although you will be undergoing physical testing, there is very little risk if you are a normal
healthy individual. Individual information obtained from this study will remain confidential. Nonidentifiable data will be used for scientific presentations and publications and you may withdraw
from the study at any time. If you have any questions please ask Jonathan Hummel before signing
this consent form.

If you have any additional questions during or after the study, Jonathan Hummel can be contacted
at:

jhummel9@live.esu

Tel: (717) 348-8373

YOU ARE MAKING A DECISION WHETHER OR NOT TO PARTICIPATE. YOUR
SIGNITURE INDICATES THAT YOU HAVE READ THE INFORMATION PROVIDED AND
YOU HAVE DECIDED TO PARTICIPATE IN THE STUDY.

I have read and understood the above explanation of the purpose and procedures for this study and
agree to participate. I also understand that I am free to withdraw my consent at any time.

Print name

Signature

Witness signature

38

Date

APPENDIX C PAR-Q+ FORM

39

APPENDIX D 7-CRITERIA WELLNESS QUESTIONNAIRE

PHYSICAL MEASURES
How would you rate your current level of fatigue?
1

2

3

4

5

How would you rate your current general muscle strain?
1

2

3

4

5

How would you rate your current pain/stiffness?
1

2

3

4

5

How would you rate your current power?
1

2

3

4

5

PSYCHOLOGICAL MEASURES
How would you rate your current sleep quality?
1

2

3

4

5

How would you rate your current level of stress?
1

2

3

4

5

How would you rate your current level of overall well-being?
1

2

3

4

5

Note: 1 = Feeling as good as possible
5 = Feeling as bad as possible

40

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