psycho-biological monitoring of health and performance...

Psycho-biological monitoring of health

and performance among endurance

athletes

Luana Chandra Justice Main

Bachelor of Science (Honours)

School of Sport Science, Exercise & Health

The University of Western Australia

This thesis is presented in fulfilment of the

requirements for the degree of Doctor of Philosophy

2009

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Overview

To date, research has endeavoured to identify reliable early-warning markers to prevent

the onset of overtraining (OT). While numerous physiological and biochemical

symptoms have been proposed as potential indicators of OT, they have not been useful

in preventing it. Therefore, there is a need for long-term monitoring studies to determine

how to prevent overtraining. This research needed to consider a range of psychological,

physiological, and immunological parameters, as they are all thought to be interrelated

in this psycho-biological phenomenon. For this research to be directly applicable for

coaches and their athletes, it was necessary to observe the athletes training, without

intervention, across an entire training and competitive year.

Central to OT is the notion of a stress and recovery imbalance (chronic exposure to

stressors). Therefore, Study 1 explored the effect of stressors (training and non-training)

experienced by triathletes, on common self-report measures of training overload (mood

disturbance and physical symptoms of training overload), athlete burnout, and the

incidence of injury and illness across an entire training and competitive year. Study 2

investigated the possible association between perceived stress and the

psychoneuroendocrine response to training overload in elite rowers. In light of the

findings of Study 1, a simple self-report training distress measure was created in Study

3; incorporating the assessment of mood disturbance, perceived stress and training-

related symptoms. Finally, Study 4 explored the possibility of a cytokine hypothesis of

overtraining. Using the training distress measure created in Study 3, the possible

association between these components of training overload and selected indices of the

inflammatory response following a period of intense and prolonged endurance training

was assessed.

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Statement of Candidate Contribution

The work involved in designing and conducting the studies described in this thesis has

been completed primarily by Luana Main (the candidate). The thesis outline and design

of the studies were developed and planned in consultation with Professor Brian

Dawson, Professor Bob Grove, and Dr Grant Landers (the candidates supervisors). The

candidate was responsible for participant recruitment, along with organisation of all

testing sessions and data collection. All blood samples were collected by the candidate.

All assay preparation for Studies 2 and 4 were completed by the candidate under the

supervision of Ms Rosanna Soares Mendes from BD Diagnostics and Dr Kathy Heel

from the Biomedical Imaging and Analysis Facility (The University of Western

Australia). Dr Kathy Heel also assisted with the FLOW cytometry analysis for both of

these studies. Mr Kevin Murray provided statistical advice in regards to the Linear

Mixed Modelling analysis method employed in Studies 1 & 4. However, all analyses

and interpretations of these results were performed by the candidate. Finally, all

research manuscripts presented here were prepared by the candidate, with the

supervisors assisting in editing the manuscripts prior to submission.

Signed:

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Table of Contents

Overview.

Statement of Candidate Contribution.

Table of Contents

Acknowledgements.

List of Publications.

List of Tables..

List of Figures.

List of Abbreviations..

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VI

VII

VIII

IX

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Chapter 1: General Introduction

1.1 Background.....

1.2 The research problem......

1.3 Objectives of the research...

1.4 Significance of the research....

1.5 References...

Chapter 2: Literature Review..

Part 1: Introduction to overtraining...

1.1 Terms and definitions......

1.2 The prevalence of overtraining

1.3 Predisposing risk factors.

1.4 The overtraining continuum....

Part 2: Signs, symptoms and measures of overtraining

2.1 Hormonal measures.

2.2 Immunological measures.

2.3 Psychological measures...

Part 3: Previously proposed mechanisms of overtraining.....

3.1 Alterations to the endocrine axis......

3.2 Metabolic hypotheses..

Part 4: Cytokines in overtraining..

4.1 The sickness response..

4.2 Exercise induced cytokine release...

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4.3 Cytokines and depression.....

4.4 The tissue trauma hypothesis of overtraining..

4.5 The Interleukin-6 hypothesis of overtraining...

Part 5: Conclusion.....

References.

Chapter 3: Study One...

Paper 1: Training patterns and negative health outcomes in triathlon:

longitudinal observations across a full competitive season......

Chapter 4: Study Two.....

Paper 2: Impact of training on changes in perceived stress and cytokine

production

Chapter 5: Study Three

Paper 3: A multi-component assessment model for monitoring training distress

among athletes.....

Chapter 6: Study Four.

Paper 4: Relationship between inflammatory cytokines and self-report

measures of training overload.

Chapter 7: Thesis Summary and Future Research Directions....

7.1 Thesis Summary..

7.2 Practical Implications......

7.3 Future Research Directions.....

7.4 References...

Appendices.

Appendix A: Study One

Appendix B: Study Two

Appendix C: Study Three..

Appendix D: Study Four...

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Acknowledgements

I would like to take this opportunity to thank and acknowledge the support of the many

individuals who have shared this journey with me.

Firstly, I would like to acknowledge my husband Tim Chambers. Many a time you

rescued me when I lost my way with my research, and you always held my hand until I

found my way again. Thank you for your unconditional support, love and rational

thinking over the years.

To my supervisors Professor Brian Dawson, Professor Bob Grove and Dr Grant

Landers, thank you for challenging me to grow. Daws, thank you for helping keep it

together over the years as coordinating supervisor, and for always telling me to just

keep at it. Grant, thank you for always being there for a chat, be it PhD, coaching, or

triathlon related. A big thank you also, for helping me to convince myself to race at the

Triathlon World Champs in Canada whilst still trying to finish. It was the opportunity

and experience of a lifetime, and Im glad I didnt let it pass by. To Bob, thank you for

being there on this journey since my honours, it was such a huge relief when our MTDS

paper was accepted. Thank you for teaching me how to respond to reviewers comments

thoughtfully and integrate new material and perspectives, where relevant.

To Dr Carmel Goodman, thank you for inspiring me to venture into the area of

overtraining all those years ago in that 3rd

year undergraduate rehab lecture; who would

have thought this was where it would end up. Thank you also for your support at the

commencement of my candidature, and input on my work since. I would also like to

acknowledge the invaluable support I received from Dr Kathy Heel and Mr Kevin

Murray. I am indebted to you for taking the time to help me find the answers in my

data.

To my family, Mum, Dad, Adelle and Alden, you never doubted my ability to complete

this work and have supported me throughout it. Your belief and confidence in me were

a constant source of encouragement. To my all my friends, and my fellow PhD crew,

thank you for all the laughs over the years, the many discussions and distractions that

you provided. To Sarah, Julie and Aditi, thank you for helping me get across that finish

line. And now, finally, I am finished, it is done!

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List of Publications

Journal Articles

Main, L.C., Landers, G., Grove, J.R., Dawson, B., & Goodman, C. (2009). Training

patterns and negative health outcomes in triathlon: longitudinal observations

across a full competitive season. Journal of Sports Medicine & Physical Fitness

(Paper submitted for publication).

Main, L.C., Dawson, B., Grove, J.R., Landers, G., & Goodman, C. (2009). Monitoring

training distress: changes in perceived stress and inflammatory cytokines.

Research in Sports Medicine, 17, 121-132.

Main, L.C., & Grove, J.R. (2009). A multi-component assessment model for monitoring

training distress among athletes. European Journal of Sport Science, 9, 191-198.

Main, L.C., Dawson, B., Heel, K., Grove, J.R., Landers, G., & Goodman, C. (2010).

Relationship between inflammatory cytokines and self-report measures of

training overload. Research in Sports Medicine, 18, 1-13.

Conference Proceedings

Main, L.C., Dawson, B., Grove, J.R., & Landers, G. (2009). Cytokines and self-report

measures of well-being in rowing. Presented at the 12th International Society of

Sport Psychology World Congress, Marrakesh, Morocco.

Main, L.C., Dawson, B., Grove, J.R., & Landers, G. (2009). Training patterns and

injury in triathlon. Presented at the 12th International Society of Sport

Psychology World Congress, Marrakesh, Morocco.

Main, L.C., Dawson, B., Grove, J.R., & Landers, G. (2007). Monitoring training

distress: changes in perceived stress and inflammatory cytokines. Presented at

the14th Australian Congress of Sports Medicine, Adelaide, Australia.

Main, L.C., Dawson, B., Grove, J.R., & Landers, G. (2007). Longitudinal monitoring of

training distress in well-trained triathletes. Presented at the 12th European

Congress of Sport Psychology, Halkidiki, Greece.

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List of Tables

Chapter 2

Table 2.1. Reported symptoms of OT (adapted from Rowbottom et al., 1998b)

Table 2.2. Changes in hormonal markers associated with OTS

Table 2.3. The effect of normal and chronic training on immune function

(adapted from Mackinnon 2000a, 2000b)

Table 2.4. A summary of proposed metabolic hypotheses

Table 2.5. The metabolism alteration process proposed by Petibois et al. (2009)

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Chapter 3

Table 1. The longitudinal effect (F-values) of potential sources of stress on

negative health outcomes

Table 2. Significant longitudinal model parameter estimates for each negative

health outcome

Table 3. Descriptive data (mean SD) for training factors averaged for each

training phase

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Chapter 4

Table 1. Mean ( SD) values for the inflammatory cytokines and perceived

stress across the 8 week training period

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Chapter 5

Table 1. Factor loadings, inter-factor correlations, and internal consistency

values for the six training distress factors

Table 2. Means ( SD) values for low, moderate, and high burnout risk

groups on each training distress factor

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Chapter 6

Table 1. Participant characteristics

Table 2. Mean ( SD) values for the inflammatory cytokines and training

distress scores (TDS)

Table 3. Significant estimates of measures of inflammatory cytokines on the

prediction of factors associated with training overload

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List of Figures

Chapter 2

Figure 2.1. Schematic representation of the relationship between training load

and performance (adapted from Lehmann et al., 1999)

Figure 2.2. Selected mechanisms underlying the genesis of OTS in endurance

sport (Lehmann et al., 1999)

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List of Abbreviations

ABQ

ACTH

ANS

BCAA

CNS

DALDA

ECSS

FSH

GAS

GH

HPA-axis

HPG-axis

HR

Ig

IL-1

IL-1ra

IL-6

IL-8

IL-10

IL-12p70

LH

mM

MAPSS

OR

OT

OTS

POMS

PSS

REST-Q

SAS

T:C

TDS

TNF-

UPS

URTIs

L

Athlete Burnout Questionnaire

Adrenocorticotropic hormone

Autonomic Nervous System

Branch Chain Amino Acids

Central Nervous System

Daily Analysis of Life Demands

European Congress of Sport Science

Follicular Stimulating Hormone

General Adaptation Syndrome

Growth Hormone

Hypothalamic-pituitary-adrenal axis

Hypothalamic-pituitary-gonadal axis

Heart Rate

Immunoglobulin

Interleukin-1

Interleukin-1 receptor antagonist

Interleukin-6

Interleukin-8

Interleukin-10

Interleukin-12p70

Luteinising Hormone

Millimolar

Mental and Physical States Scale

Overreaching

Overtraining

Overtraining Syndrome

Profile of Mood States

Perceived Stress Scale

Recovery Stress Questionnaire

Signs and Symptoms

Testosterone and Cortisol ratio

Training Distress Scale

Tumor Necrosis Factor-

Under Performance Syndrome

Upper Respiratory Tract Infections

Micro Litres

Chapter 1: General Introduction

Chapter 1 General Introduction

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1.1 Background

Historically, stress has been defined by a series of physiological changes, including

activation of the hypothalamic-pituitary-adrenal (HPA) axis, as well as changes in the

autonomic nervous system (ANS). The neurobiological regulation of responding to

stressful events is a well-studied, and yet poorly understood, physiological

phenomenon. This confusion is due in part to the different definitions of stress that

exist, but also to individual variability in responding to a stressor. Often what is

perceived as a threat and evokes a physiological stress response in one person may not

be stressful (perceptually or physically) to another; and yet chronic exposure to stress

has a significant impact on virtually every system in the body. To date,

psychobiological investigations conducted in sport and exercise have combined

assessments of mood states and stress hormones to examine the beneficial effects of

exercise, with evidence of significant relationships being reported. However, optimising

athletic performance represents the primary aim of the majority of sport science

research, and as athletes engage in prolonged periods of heavy training, they increase

their risk of suffering from a range of negative health outcomes. Therefore, a

psychobiological approach has been considered to explain the impact of overtraining

(OT).

Exposure to a variety of stressors triggers the immune system, which in many ways

operates as a sensory organ for the brain. This feedback loop, allows the activation of

the immune cells to produce the physiological, behavioural, affective and cognitive

changes that are collectively called sickness (Maier & Watkins, 1998, p.83). Many of

the signs and symptoms commonly associated with OT may clearly be initiated by the

action of inflammatory cytokines. Two specific hypotheses have been presented

implicating cytokines in the aetiology of OT, namely Smiths (2000; 2004) tissue


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trauma hypothesis, and Robsons (2003) Interleukin-6 hypothesis. However, data on

training of competitive athletes and the cytokine mediated inflammatory response is

limited and further research is required.

1.2 The research problem

It is well supported that OT occurs when there is an imbalance between the stressors

imposed upon an athlete, and the athletes ability to adapt to or cope with these

stressors. The most notable sign of OT is a decrement in performance, despite continued

or increased training, together with symptoms of chronic fatigue which may persist

despite a brief recovery period of a few days. However, it is possible that other signs

and symptoms typically associated with OT are evident before deterioration in

performance. To date, no single factor or group of factors (biochemical, psychological,

physiological or other) has been shown to differentiate between effective intense

training and OT. Similarly, no factor has been confirmed as useful for the monitoring of

training, prevention of Overtraining Syndrome (OTS), or elucidation of the mechanisms

behind OT.

A variety of hypotheses have been proposed to explain the OTS, and while a number of

these remain viable, others have failed to gain support. It has been suggested that many

hypotheses represent pertinent aspects of the OTS, yet individually fail to account for

all observed changes. Furthermore, prediction and interpretation of performance

changes is often confusing as not all aspects of performance are affected simultaneously

nor are they impacted to the same degree.

1.3 Objectives of the research

The primary aim of this thesis was to investigate the relationship between prolonged

exposure to stressors (both training and life stressors) and the experience of associated


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negative health outcomes in endurance athletes. In addition to OT, other negative health

outcomes which have also been associated with an inability to adapt or cope with

imposed stressors include athlete burnout, injury and illness. Interrelationships between

these possible outcomes of the chronic exposure to stress and OT require further

research. Specifically, the role of training factors and general life stressors on the

development or occurrence of each of these states has yet to be examined. The second

key objective of this research project was to explore the possible association between

measures of perceived stress, mood disturbance and symptoms of OT, with selected

indices of the inflammatory response following periods of intense and prolonged

endurance training. Specifically, the aims of this thesis were to:

Identify whether exposure to stressors (either training factors or global life

stressors) had a significant effect on the experience of, or risk of suffering from

various negative health outcomes in the sport of triathlon, including the risk of

injury and illness, OT and athlete burnout.

Explore the possible association between perceived stress and selected indices of

the inflammatory response following a period of intense and prolonged

endurance training.

Create a simple self-report training distress measure that: (1) included an

assessment of mood disturbance, perceived stress and training-related

symptoms; (2) reflected both the frequency and intensity of these distress

dimensions; and (3) discriminated between groups of athletes with higher or

lower risk of developing problems as a result of training overload.

Explore the possible association between perceived stress, measures of mood

disturbance, symptoms of training overload (as measured by the inventory


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created in Study 3), and selected indices of the inflammatory response following

a period of intense and prolonged endurance training.

1.4 Significance of the research

Theoretically, the associated signs and symptoms of OT may be explained from a

psycho-immuno-biological standpoint, with all major systems of the body being

affected by, or involved in the development of symptoms. Two specific hypotheses

have been presented implicating cytokines in the aetiology of OT; however, data on the

training of competitive athletes and the inflammatory response is limited. Therefore,

examination of the role of inflammatory cytokines and exposure to stressors warrants

investigation with the long-term objective to both provide an explanation for the

aetiology of OT, as well as identify a marker, or series of markers to monitor training

responses.

This combined approach appeared to be the logical progression in the research process

and will help provide a better understanding of the interaction between physiological

and psychological components of OT. In addition, psychological monitoring to date has

generally focused on single measures, so the proposed multi-component approach is

unique. Potentially, the results of the research will be useful for coaches, athletes and

medical personnel who are responsible for preventing and managing OTS.


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1.5 References

Maier, S. F., & Watkins, L. R. (1998). Cytokines for psychologists: implications of

bidirectional immune-to-brain communication for understanding behaviour,

mood, and cognition. Psychological Review, 105, 83-107.

Robson, P. J. (2003). Elucidating the unexplained underperformance syndrome in

endurance athletes: the interleukin-6 hypothesis. Sports Medicine, 33, 771-781.

Smith, L. L. (2000) Cytokine hypothesis of overtraining: a physiological adaptation to

excessive stress? Medicine & Science in Sport & Exercise, 32, 317-331.

Smith, L. L. (2004). Tissue trauma: The underlying cause of overtraining syndrome?

Journal of Strength & Conditioning Research, 18, 185193.

Chapter 2: Literature Review

Chapter 2 Literature Review

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Part 1: Introduction to overtraining

1.1 Terms and definitions

Due to the nature of the overtraining (OT) phenomenon, research in this area has been

plagued by a number of uncertainties and shortcomings. One of the greatest problems

has been the number of different definitions that exist. This, coupled with inconsistent

terminology usage has hindered the comparison of results from previous research

studies. Perhaps because of the complexity of the overtraining syndrome (OTS),

considerable variation exists in the terms used to describe this phenomenon.

Overreaching (OR), OT, OTS, staleness, overload, underperformance, under-recovery,

short- and long-term OT, and more recently, the under-performance syndrome (UPS;

Budgett et al., 2000) have all been used by different researchers to describe, define and

discuss what appears to be aspects of the same phenomenon.

Historically, OTS was referred to as staleness by researchers in the United States

(Hackney, Pearmann, & Nowacki, 1990), while researchers in Europe tended to use the

term OT to describe the same phenomenon (Kuipers & Keizer, 1988). Further

complications arose due to a lack of differentiation by researchers between the process

and outcome. Morgan, Brown, Raglin, OConnor and Ellickson (1987a) regarded

staleness as the outcome of periods of unsuccessful overload training, while Silva

(1990) suggested that the phenomenon should be differentiated into stages from

staleness to OT and finally, burnout.

1.1.1 Overreaching & Overtraining

When discussing OT, it is important to differentiate it from OR, which is a transient

period of reduced athletic performance. Indeed, OR can be a deliberate process resulting

from periods of specific overload training, with the purpose of eliciting performance


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gains (Steinacker & Lehmann, 2002). With a brief recovery period of a few days,

performance capacity can generally be fully restored. Many recent papers have referred

to, and adopted the definitions presented by Kreider, Fry and OToole (1998a). As such,

OR has been defined as:

An accumulation of training and/or non-training stress resulting in a short-term

decrement in performance capacity with or without related physiological and

psychological signs and symptoms of OT, in which restoration of performance

capacity may take several days to several weeks. (p. viii)

In contrast, OT has been defined as:

An accumulation of training and/or non-training stress resulting in a long-term

decrement in performance capacity with or without related physiological and

psychological signs and symptoms of OT, in which restoration of performance

capacity may take several weeks or months. (p. viii)

It should be noted that the critical factor in both these definitions is the duration of the

decrease in performance capacity, with the difference being the time taken to restore

optimum performance. While these definitions are not entirely satisfactory, they have

provided the most accurate description of the conditions to date and are frequently cited

in the literature (Halson & Jeukendrup, 2004). However, these definitions suggest that

the difference between OR and OT is the amount of time required for recovery, not the

type or duration of training stress experienced (Budgett et al., 2000; Lehmann, Foster,

Gastmann, Keizer, & Steinacker, 1999). These definitions also imply that it is possible

to experience these two states without the presence of psychological disturbances and

physiological signs and symptoms.


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Meeusen and colleagues (2006) suggested that there are actually two forms of OR, one

that is functional (as discussed above) and the other that is non-functional. Periods of

intensified training, in the context of training periodisation, or during a training camp

for example, are commonly included in athletes training programs to induce a super-

compensation effect. This successfully occurs when appropriate periods of recovery are

observed and the athlete exhibits an enhanced performance compared to baseline levels

(Steinacker, Lormes, Reissnecker, & Liu, 2004). In this situation, the physiological

responses compensate the training-related stress, and may be referred to as short-term

OT or functional-OR.

In comparison, Meeusen and colleagues (2006) suggested that non-functional OR

represents the point where the first signs of prolonged training distress and hormonal

disturbances occur. At this point it was suggested that several confounding factors such

as inadequate nutrition, illness, psychosocial stressors and sleep disorders may be

present. Therefore, differentiation between OR and OTS at this stage would be very

difficult and would depend on the results of clinical diagnosis. Given these difficulties,

Meeusen and colleagues (2006) felt that diagnosis of OTS could only be made

retrospectively when the time course for recovery can be overseen. As such, it was

suggested that OTS may be best considered as the prolonged maladaptation of several

biological, metabolic, neurochemical and hormonal regulation mechanisms (Meeusen et

al., 2006; Petibois, Cazorla, Poortmans, & Deleris, 2003b).

1.1.2 Under Performance Syndrome

Due to the inherent confusion surrounding the OT phenomenon, a round table

discussion was held in 1999 to discuss the diagnostic criteria to be used in the future.

Budgett and colleagues (2000) felt that the term OTS was inappropriate as it implied

that excessive exercise was the sole causative factor, whereas its aetiology appears


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multi-factorial. Concern has been raised that assuming OTS is solely caused by

excessive exercise could limit further investigations into the aetiology of the syndrome

(Robson, 2003). As such, the OTS was redefined as the UPS, or more specifically a

persistent, unexplained performance deficit (recognised and agreed by coach and

athlete) despite two weeks of relative rest (Budgett et al., 2000, p. 67). It should be

noted that the critical factor in describing UPS is still a decrease in performance

capacity, although this definition recognises that the cause of the underperformance and

chronic fatigue is not necessarily solely related to the training load.

1.1.3 Athlete Burnout

Originally coined by clinical psychologist Herbert Freudenberger in 1974, burnout was

used to describe stress responses among staff members of clinical institutions. The

original burnout literature was from the human services domain, where there was social

interaction between a provider and a recipient. Referring to the processes surrounding

stress overload, burnout is grounded in a psychosocial framework, where excessive

physical stressors are possible but not requisite antecedents. Most burnout research has

been based on Maslach and Jacksons (1981) definition of burnout as a stress reaction

syndrome comprised of three dimensions: emotional exhaustion, depersonalisation, and

associated feelings of low personal accomplishment. Currently, burnout is proposed to

be the result of chronic psychosocial stress, and has been associated with attentional

difficulties (Van Der Linden, Keijsers, Eling, & Schaijk, 2005).

Sport scientists have suggested that the negative, unmotivated and exhausted states

sometimes described by athletes are a sport-related manifestation of the burnout

syndrome (Gould, Tuffey, Udry, & Loehr, 1997). While burnout is a commonly used

term within the sporting community, there is much debate as to the definition and


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measurement of athlete burnout (Raedeke & Smith, 2001). To date, three main

operational definitions of athlete burnout have been presented.

The first, Smiths (1986) cognitive-affective model of athlete burnout, is conceptually

grounded in social exchange theory (Thibaut & Kelley, 1959). This description of

athlete burnout emphasizes imbalances between demands and resources, and the

cognitive appraisal of the perceived imbalance. In comparison, Silva (1990) presented

athlete burnout as the endpoint of excessive physical training. Silva proposed that the

negative responses to overload training lie on a continuum from staleness to OT, and

finally to burnout. Therefore, it is an initial failure of the bodys adaptive mechanisms

in responding to psycho-physiological stress created by training stimuli (Silva, 1990,

p.10) that is the entry point to the continuum. Burnout in this definition is the ultimate

consequence of the chronic experience of OT; with Silva suggesting that withdrawal

from sport involvement is an inevitable consequence of burnout.

Coakley (1992) described athletic burnout as a physical withdrawal from sport

following an intense investment of effort and high achievement. This conceptualisation

focuses upon burnout as something particular to those whose achievements are

exceptional in some way. It also views psychosocial stress as a consequence of the

process leading to sport withdrawal (i.e., burnout in Coakleys terms), rather than a

cause of sport burnout as described in other commentaries (e.g. Raedeke, 1997; Smith,

1986). This difference of opinion may explain partly why researchers investigating

athlete burnout have often confounded the antecedents, characteristics, and

consequences of the burnout syndrome (Cresswell & Eklund, 2006). Researchers are

currently investigating a motivational approach to the study of burnout in elite athletes

(Cresswell & Eklund, 2007; Lemyre, Treasure, & Roberts, 2006; Lemyre, Roberts, &

Stray-Gundersen, 2007). For example, Lemyre,et al. (2007) suggested that self-


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determined motivation and symptoms of overtraining were both independently linked to

signs of burnout in elite athletes. Although no moderating effect was found, pairing self-

determined motivation with symptoms of overtraining at the start of the winter sport

season increased the prediction of burnout in elite athletes at the end of the season.

The confusion surrounding burnout and OT is understandable as both terms are

independently shrouded in some confusion, and clear, universally-accepted definitions

have not been determined. Of most concern is the assumption that burnout is the

ultimate outcome of the OT process, with withdrawal from sport as the inevitable

endpoint (Silva, 1990). This assumption should be viewed with caution. While the

burnout concept has indeed been successfully integrated into sport research (Smith,

1986; Cresswell & Eklund, 2007), it is at this point inappropriate to use the terms

burnout and OT interchangeably. For this reason, Smiths (1986) definition of burnout

will be adopted for the current discussion, with withdrawal from sport as one of the

many possible consequences.

1.1.4 Conclusions regarding terminology

Given the confusion in the literature to date, and the numerous attempts that have been

made for uniformity of terms, deciding the terms and definitions to be used for the

current research program becomes somewhat difficult. Overload training will be used as

a noun, to describe the type of intensified training; while the term OR will be

considered synonymous with Meusen and colleagues (2006) short-term functional OR.

As such, it will refer to an accumulation of training and/or non-training stress resulting

in a desired short-term decrement in performance capacity with improved performance

following a rest period. Related physiological and psychological signs and symptoms of

OT may or may not be present, and restoration of performance capacity may take up to

14 days.


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Overtraining will be used as an adjective to describe both the process and the

accumulation of training and/or non-training stress beyond overreaching. Training

distress will be employed in reference to the psychological and behavioural response to

(or outcome of) OT.

Overtraining syndrome (OTS) will be considered the ultimate outcome of the OT

process, at which point the athlete is forced to withdraw from training and competition,

until they are physically able to resume participation. Specifically, it will be defined as a

chronic accumulation of training and non-training stressors, resulting in a decrement of

performance capacity with prolonged maladaptation of several biological,

neurochemical, hormonal and metabolic regulation mechanisms. This will commonly

result in physiological and psychological signs and symptoms of OT in which

restoration of performance capacity may take several months. It is hoped that this use of

terminology will be viewed as consistent with Kreider and colleagues (1998b), while

also agreeing with Meeusen and colleagues (2006) position statement made on behalf of

the European Congress of Sport Science.

1.2 The prevalence of overtraining

The prevalence of OTS in different sports has not yet been clearly established. This may

partly be due to the number of different definitions of OT that exist, coupled with

inconsistent terminology usage which has hindered the ability to compare the results of

previous research studies. However, it has been estimated that 65% of all long-distance

runners will be affected by OTS at some time during their competitive career

(McKenzie, 1999). These findings are consistent with the earlier work of Morgan and

colleagues with elite distance runners which reported that reported that 64% of males

(Morgan, OConnor, Ellickson, & Bradley, 1988b) and 60% of females (Morgan,


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OConnor, Sparling, & Pate, 1987b) indicated they had experienced OT at some point

during their careers.

Over a shorter timeframe, Gould et al. (1999) reported that 28% of the 296 strong

United States Atlanta Summer Olympic team, and 10% of their 83 member Nagano

Winter Olympic team reported that they were overtrained in the 90 days prior to the

Olympics. Yet a clear definition of OT was not provided to the athletes prior to

responding to the statement I overtrained in preparation for the Olympics (p. 181);

and given the frequent colloquial use of the term OT, these prevalence statistics should

be interpreted with caution.

Raglin, Sawamura, Alexiou, Hassmn, and Kentt (2000) reported that from a sample

spanning across four countries an average of 35% of young swimmers reported

experiencing performance decrements for at least two weeks during their swimming

careers, which was not a result of injury or illness, but rather due to training (20% from

Sweden, 24% from USA, 34% from Japan, and 45% from Greece). While the accuracy

of the recall ability of these young swimmers may be questioned, these figures are

similar to those reported by Hooper and colleagues (1995), who indicated that

approximately 21% of swimmers were identified as overtrained following the

Australian National swim titles. Thus, it is clear that while exact prevalence figures are

not yet available, OT will affect a significant number of athletes at some point during

their athletic career. Further research to explore pre-disposing risk factors, early

warning signs and methods for monitoring training overload is therefore certainly

warranted.


Page | 16

1.3 Predisposing risk factors

Numerous researchers, including Armstrong and Van Heest (2002) have noted that the

border between optimal performance and performance impairment due to OT is subtle

(p. 341). Consequently, many researchers have explored a number of risk factors which

may contribute to, or prolong the experience of OT. Factors which have been identified

may be loosely grouped into one of three possible categories: 1) training issues; 2)

situational and environmental stressors; and 3) athlete issues. Athlete issues may be

separated into two further sub categories: a) physical issues and b) beliefs, behaviours

and attitudes (Richardson, 2006). While an in-depth analysis of the literature regarding

each predisposing risk factor identified is beyond the scope of this review, a brief

discussion of key factors within each category will be presented.

Training issues are probably the most commonly cited risk factors in terms of the

development of OT. Of particular note is high volume or high intensity training, which

has received a great deal of attention (e.g. Budgett, 1990; Kentt & Hassmn, 2002;

Kuipers, 1996; Uusitalo, 2001). For example, Lehmann and colleagues (1992) explored

the influence of an increase in training volume versus an increase in training intensity

on running performance. Two studies were carried out with eight and nine experienced

middle-or long distance runners, with experimental training periods lasting for three

weeks. Results indicated that an increase in training intensity produced an improvement

in running velocity at 4 mM lactate concentration and in total running distance in the

incremental test. In comparison, the increase in training volume study protocol resulted

in stagnation of running velocity at 4 mM lactate concentration and a decrease in total

running distance in the incremental test. It was suggested that the associated changes in

metabolism and catecholamine measures may have indicated an exhaustion syndrome


Page | 17

(OR) in the athletes from the increased training volume study; however, this hypothesis

requires further research (Lehmann et al., 1992).

Other possible training risk factors that have been proposed include training monotony,

lack of periodisation, and/or a failure to include adequate recovery into the training

program (Kreider et al., 1998b). Sudden increases in training load or volume,

specifically during transition periods within a training year, may also predispose

athletes to OT (Budgett, 1990; Hawley & Schoene, 2003; Uusitalo, 2001). One

significant risk factor is a lack of monitoring for signs and symptoms of OT (Hooper &

Mackinnon, 1995). If athletes and coaches are aware of the early warning signs, then

preventative measures can be taken and any increased risk of OT may be reduced.

Therefore, it is clear that the type of training greatly influences the performance

outcome. At the same time, training factors alone are not the only contributors to the

development of OT. Situational and environmental stressors may also have a significant

impact on an athletes ability to respond to training stimuli. For example, poor nutrition

(Costill et al., 1988), travel (especially across time zones) and jet lag can have a

significant impact on athletic performance (Rushall, 1990), particularly combined with

changes in training environment, altitude, temperature and or humidity (Hug, Mullis,

Vogt, Ventura, & Hoppeler, 2003). Conflicts with coaches, team-mates, friends or

parents within an athletes sporting involvement may also contribute to the development

of a training stress state (e.g. Hollander & Meyers, 1995; Kentt & Hassmn, 2002;

Kuipers & Keizer, 1988). In addition to these stressors, athletes may also be subjected

to stressors external to their sport environment. For example, work, study or relationship

stressors may also affect an athletes ability to train and respond to the training stressors

(Rushall, 1990).


Page | 18

Finally, issues suffered by the athlete may also increase their risk of OT. For example, it

has been suggested that premature return from injury (Budgett, 1990); poor or

inadequate sleep (Kentt & Hassmn, 2002; Uusitalo, 2001); and poor or inadequate

nutrition (Berning, 1998) (e.g. caloric restriction, insufficient carbohydrate intake, iron

deficiency); may all impact on an athletes ability to cope with and positively adapt to

imposed training loads. While these factors are possible additional stressors, there is

insufficient support for most of these as potential triggers initiating an OT response.

Furthermore, identifying these possible pre-disposing risk factors, sometimes referred to

as initiating events, has not revealed the mechanisms of OTS (Kreider, Fry, & OToole,

1998a).

1.4 The overtraining continuum

Endurance exercise induces a variety of physiological and metabolic adaptations in

skeletal muscle that function to minimise cellular disturbances during subsequent

training sessions (Hawley, 2002). In order to optimise performance and ensure the

desired physiological adaptations are achieved, it is necessary to determine the

appropriate stimulus required. The key components of a training program are the

volume/duration, frequency and intensity of training sessions. Taken collectively, these

components are the training stimulus, the manipulation of which will alter the ultimate

performance outcome/response.

It is evident that underestimation or overestimation of training load and performance

level, together with insufficient recovery, will lead to inappropriate training responses

of the athlete (Steinacker et al., 2000). Optimal training is achieved when an athlete

progressively overloads, and positive physical adaptation occurs through a gradual

development of the capacities required to tolerate the stimulus. While it is apparent that

repeated bouts of exercise are essential to achieve the cumulative stress necessary to


Page | 19

induce the metabolic and morphological adaptations in skeletal muscle, training that is

of an intensity greater than the body can cope with will achieve the reverse effect, as is

evidenced in Figure 2.1.

Figure 2.1: Schematic representation of the relationship between training load and

performance (adapted from Lehmann et al., 1999)

Steinacker and colleagues (2000) demonstrated that clear signs of OR were found after

18 days of intense training. Specifically, high training loads of approximately 3.2 hours

per day were sustained for 18 days prior to the 1995 Rowing World Championships in

10 junior elite rowers and reserves, with decreases in performance, gonadal and

hypothalamic steroid hormones. Also noted was a deterioration of recovery as measured

by the Recovery-Stress-Questionnaire for Athletes (REST-Q Sport; Kellmann & Kallus,

2000). Following a recovery period of two to three weeks, maximum performance and

endurance were improved, and all hormone measures improved. Steinacker and

colleagues concluded that the data from this study confirms that the critical borderline

to acute OT/OTS in adapted endurance athletes may be around three weeks of

intensified or prolonged training lasting three hours per day.


Page | 20

Part 2: Signs, symptoms and measures of overtraining

It is interesting to note that research discussing possible markers of OT can be

objectively examined, while much of the literature on the symptoms of OT is

predominantly based on anecdotal reports. In addition, much of the research regarding

OT involves studies that have examined athletes in a state of OR, or acute-short term

OT, as it is unethical to intentionally induce a state of full OT (i.e. OTS/UPS). The

question remains as to whether the signs and symptoms that are observed during these

intervention studies are indeed the same as those associated with anecdotal reports of

athletes who are experiencing OTS (Halson & Jeukendrup, 2004). Fry, Morton and

Keast (1991) presented a comprehensive table of the major symptoms of OT, as

indicated by their prevalence in the literature. Rowbottom, Keast and Morton (1998b)

later presented a very similar list of symptoms (Table 2.1) with greater distinction

between sub-categories, illustrating the increased involvement of researchers from

different disciplines investigating the area of OT. Although these observed

physiological measures have been effective in confirming the OTS, they have not been

useful in preventing it. This is partly due to uncertainty about whether the symptoms

noted precede OT or are merely manifestations of the OTS (Fry et al., 1991).

2.1 Hormonal measures

For several years it has been hypothesized that a hormone-mediated central deregulation

occurs during the pathogenesis of the OTS. Numerous hormonal indices have been

proposed as possible markers for monitoring OT and have been extensively examined

(e.g. Lac & Maso, 2004). In particular, cortisol and testosterone have been identified as

reliable markers of training stress (e.g. Filaire, Bernain, Sangol, & Lac, 2001; Kraemer

et al., 2004; Maso, Lac, Filaire, Michaux, & Robert, 2004; Mackinnon & Hooper, 1991;

Page | 21

Table 2.1: Reported symptoms of OT (adapted from Rowbottom et al., 1998b)

Performance/physiological:

Decreased performance in competition

Decreased performance in training

Reduced tolerance of training load

Increased fatigue during exercise

Prolonged fatigue

Decreased muscular strength

Decreased maximum work capacity

Chronic fatigue

Decreased muscle glycogen

Decreased maximal lactate

Elevated basal metabolic rate

Sensorimotor performance:

Loss of coordination

Decreased mechanical efficiency

Loss of muscle tone

Poor muscular control and balance

Slow sensory motor performance

Lengthened decision/reaction times

General clumsiness

Nutritional disorders:

Loss of appetite

Gastrointestinal and digestive disorders

Feelings of thirst

Increased fluid intake

Mineral and vitamin deficiencies

Cardiorespiratory function:

Increased heart rate

Higher heart rate at standard work load

Decreased maximum heart rate

Abnormal t-wave pattern in ECG

Elevated blood pressure

Shortness of breath

Increased frequency of respiration

Haematology:

Decreased haemoglobin

Decreased serum iron

Decreased serum ferritin

Decreased red blood cell count

Decreased hematocrit

Biochemistry:

Elevated plasma creatine kinase

Elevated plasma urea

Elevated plasma 3-methylhistidine

Increased uric acid production

Depressed plasma glutamine

Hormones:

Hypothalamic dysfunction

Elevated plasma catecholamines

Elevated serum cortisol

Depressed serum testosterone

Immunology:

Increased susceptibility to and severity of

infections/ colds/ allergies

Frequent persistent cold/flu-like

symptoms

Sore throats

Glandular fever

Minor scratches heal slowly

Swelling of lymph glands

Decreased serum immunoglobulin

Decreased salivary immunoglobulin a

Decreased white blood cell count

Decreased lymphocyte count

Reduced mitogen responses

Physical complaints:

Cold hands and feet

Headaches

Nausea

Backaches

Decreased body fat

Sleep problems:

Insomnia

Sleep disturbances

Problems falling asleep

Night sweats

Musculoskeletal complaints:

Increased incidence of injury

Muscle pain

Muscle soreness/ stiffness

Stress fractures

Joint pain

Muscle damage

Psychological symptoms:

Feelings of depression

Anxiety

General apathy

Increased anxiety

Increased perceived effort

Decreased self esteem

Lethargy

Decreased energy/ vigour

Loss of enthusiasm

Lack of interest in competition and

training

Difficulty in concentrating at training

Loss of libido

Page | 22

Mackinnon, 1996; Rowbottom et al., 1997; Urhausen et al., 1998a). Application of the

urinary cortisol/cortisone ratio has also received attention for its use in monitoring

swimmers (Atlaoui et al., 2004). Plasma catecholamines have also been presented as a

possible marker, with Hooper and colleagues (1995) suggesting that adrenaline and

noradrenaline may provide an objective means of diagnosing the OTS when considered

in conjunction with the athlete's self-assessment of well-being. A brief summary of

research findings is presented in Table 2.2.

Results from research in this area are far from clear. One reason for this is differences in

measuring methods, and/or detection limits of the analytical equipment used. While

hormones provide interesting diagnostic information, they remain unsuitable for

practical application, as results require clinical analyses that are not readily available to

all athletic bodies (Hug et al., 2003). These inconsistent findings and the inability to

distinguish acute fatigue resulting from intensified training from OT do not support the

use of the majority of biochemical markers as diagnostic tools. Uusitalo (2001)

commented that:

Hormonal changes have not proven to be sensitive or specific indicators of the

OT state... reliable measures of hormone levels during maximal exercise require

appropriate lab conditions, which are not always possible. For results to be

meaningful, identical collection, transportation, storage, and protocols of

analysis must be observed. (p.9)

Thus, it remains difficult to draw conclusions about possible changes in hormone

concentrations. It is hoped that future developments in technology, improvements in

testing conditions and controlled training programs, will allow further growth of

understanding in this area.


Page | 23

Table 2.2: Changes in hormone markers associated with OTS

Variable

After intense training

not causing OT/OR

After intense training causing

OT/OR

ACTH

Increase Rietjens et al. (2005)

Decrease Barron et al. (1985)

Urhausen et al. (1998a)

Meeusen et al. (2004)

Catecholamines

Decrease Atlaoui et al. (2006)

Mujika et al. (1996)

Increase Fry et al. (1994a)

Atlaoui et al. (2006)


Decrease Uusitalo (1998)

Cortisol

Increase Atlaoui et al. (2004)

Filarie et al. (2001)

Suzuki et al, (2000)

Tyndall et al. (1996) () Decrease Tyndall et al. (1996) () No change Filarie et al. (2004)


Rowbottom et al. (1997)

Increase Coutts et al. (2007)


Decrease Atlaoui et al. (2004)

Fry et al. (1992a)


Rietjens et al. (2005)

Steinacker et al. (2000)

GH

Increase Suzuki et al. (2000) Increase Rietjens et al. (2005)



Urhausen et al. (1998)

Prolactin

Increase Suzuki et al. (2000)




FSH

Decrease Steinacker et al. (2000)

No change Fry et al. (1992a)


LH

No change Mujika et al. (1996)

Decrease Steinacker et al. (2000)

No change Fry et al. (1992a)


T:C ratio

Decrease Filarie et al. (2001)

No change Hug et al. (2003)

Filarie et al. (2004)


Decrease Coutts et al. (2007)

No change Fry et al. (1992)

Testosterone

Decrease Filarie et al. (2001)

Tyndall et al. (1996)

No change Filarie et al. (2004)



Increase Urhausen et al. (1998)

Decrease Coutts et al. (2007)


No change Fry et al. (1992)

Note: Hormone abbreviations, ACTH: adrenocorticotropic hormone; GH: Growth hormone;

FSH: follicular stimulating hormone; LH: luteinising hormone; T:C ratio: testosterone and

cortisol ratio.


Page | 24

2.2 Immunological measures

Anecdotal reports have linked periods of heavy training, sometimes associated with

prolonged fatigue and underperformance, with susceptibility to infections. In two

independent review papers, both MacKinnon (2000a) and Nieman (1998) concluded

that while overtrained athletes are not immune deficient by clinical standards, they are

susceptible or at an increased risk of suffering from upper respiratory tract infections

(URTIs) during periods of heavy training, and the 1-2 weeks following prolonged

intense aerobic exercise training. To date, research investigating the role of the immune

system in OTS has focused on one of three primary issues:

1. The association between OR/OT and an increased incidence of infection

2. Monitoring of leukocytes and other immune factors during periods of OT

3. The possibility that disease and infections may increase the risk of OTS.

Yet despite the variety of measures examined, there is still uncertainty about the effect

of exercise and training on immune function, which may depend on the pre-existing

state of the athlete and the type of exercise. Mackinnon (2000a, 2000b) presented two

very comprehensive review tables summarising available research on the effects of OT

on immunity and performance. A compilation of these two review tables is presented in

Table 2.3 as a summary of the research findings in this area. For further explanation on

any of the markers presented, the reader is referred to the studies referenced in Table 2.3

as it is beyond the scope of this review. Therefore, while immune markers do not appear

to be reliable markers of impending OT, recurrent infections and immunodepression are

common among overtrained athletes. It has been purported that cytokines may play a

role in the aetiology of OT, which would explain a number of the findings to date;

however, this will be discussed in greater detail in Part 4.

Page | 25

Table 2.3: The effect of normal and chronic training on immune function (adapted from Mackinnon 2000a, 2000b)

Immune parameter Resting values in athletes After normal or moderate training After intense training not causing

OT/OR


OT/OR

Leukocyte number Normal

Hooper et al. (1995)

Gleeson et al. (1995)

Nieman (1994)

No change

Baum et al. (1994)

Nehlsen-Cannarella et al. (1991)

No change



Or decrease

Hack et al. (1997)

Lehman et al. (1996)

No change

Mackinnon et al. (1997)

Or decrease


Granulocyte number Normal

Pyne et al. (1995)

Nieman et al. (1995a)

No change

Baum et al. (1994)

Mitchel et al. (1996)


No change or slight increase

Bury et al. (1998)


Pyne et al. (1995)

Increase


Lymphocyte number Normal




Nieman et al. (1995b)

No change


Baum et al. (1994)

No change

Fry et al. (1992b)



Or decrease

Hack et al. (1997)

No change

Fry et al. (1992b)

Or transitory decrease


Natural killer cell number Normal



Or increase


Rhind et al. (1994)

No change

Nieman et al. (1990)

Tvede et al. (1991)

No change

Baj et al. (1994)

Or decrease

Fry et al. (1994)

Gedge et al. (1997)


Decrease

Fry et al. (1992)

Leukocyte adhesion molecule

expression

Increase

Baum et al. (1994)

Increase

Baum et al. (1994)

Increase

Baum et al. (1994)

-

Neutrophil function

Lower

Bury & Pirnay (1995)

Pyne et al. (1995)

Smith et al. (1990)

No change

Hack et al. (1994)

Decrease

Bury et al. (1998)

Hack et al. (1994)

Pyne et al. (1995)

Smith et al. (1990)

No current data available

Page | 26

Table 2.3 (cont.): The effect of normal and chronic training on immune function

Lymphocyte activation or

proliferation

Normal

Gedge & Mackinnon (1998)



Or increase

Rhind et al. (1994)

No change


Mitchell et al. (1996)


Or decrease

Bury et al. (1998)


Increase

Baj et al. (1994)

Baum et al. (1994)

Fry et al. (1992b)

Hack et al. (1997)

Increase

Immune parameter Resting values in athletes After normal or moderate training After intense training not causing

OT/OR


OT/OR

Natural killer cytotoxic action Normal


Or increase


Pedersen et al. (1989)

Increase


Or no change

Bury et al. (1998)

Decrease

Gedge et al. (1997)


Serum Ig concentration In the lowest 10% clinical norms


No change

Mitchell et al. (1996)


No change



Serum specific antibody Normal

Bruunsgaard et al. (1997)


No effect on ability to mount

specific antibody response


(elderly female subjects)


Mucosal Ig-A concentration Normal



Or low Tomasi et al. (1982)


Mackinnon & Hooper (1994)

No change

McDowell et al. (1992)

No change


Or decrease as intensity increased


Tharp & Barnes (1990)

No change


Plasma glutamine concentration Clinically normal

Keast et al. (1995)


But lower in overtrained athletes

Mackinnon &Hooper (1996)


No change



Or decrease

Hack et al. (1997)

Keast et al. (1995)

Decrease

Keast et al. (1995)

Or no change



Key: Ig - immunoglobulin; Ig-A = Immunoglobulin-A


Page | 27

2.3 Psychological measures

While numerous physiological and biochemical symptoms have been proposed as

potential indicators of OT, few have proven to be consistent across different studies

involving different athletic groups. As such there is no single parameter available to

predict or diagnose OT (Hartmann & Mester, 2000). Conversely, stronger and more

consistent relationships have been observed with self-report measures. Indeed, there is

general agreement that OT is characterised by a marked increase in negative affective

states, such as anxiety and depression (Morgan, 1985; Morgan et al., 1987a;

Tenenbaum, Jones, Kitsantas, Sacks, & Berwick, 2003a, 2003b; Veale, 1991). Self-

report measures exhibit reliable dose-response relationships with training load, and

appear to be sensitive to the symptoms of both short-term and long-term training

distress across a range of different sports (Morgan et al., 1987a; Raglin & Morgan,

1994; Raglin & Wilson, 2000).

Existing approaches to the monitoring of training state via self-report can be placed into

three categories based on the primary psychological parameter examined. The classic

approach has been monitoring of mood disturbances with the Profile of Mood States

(POMS; McNair, Lorr, & Dropplemann, 1971). A second approach has been to focus on

the magnitude of training-specific symptoms (Fry et al., 1994; Morgan, Costill, Flynn,

Raglin, & O'Connor, 1988a), while the third approach has been to examine changes in

perceived stress (Kellmann & Kallus, 2001; Rushall, 1990). These self-report measures

have the added advantages of being efficient, inexpensive, non-invasive, and can easily

be administered by coaching staff or team personnel to monitor athletes progress

throughout a training and competitive year.


Page | 28

2.3.1 Mood disturbance

To date there has been substantial research undertaken on mood fluctuations in

connection with changes in training volume. Indeed, the single most consistent finding

reported in the OT literature is that increases in training load are associated with shifts

towards negative mood states, while reductions in training loads are associated with

improvements in mood (Hooper, MacKinnon, & Hanrahan, 1997; Hooper et al., 1995).

Based on the findings of this research, monitoring of mood fluctuations has been

frequently proposed as a useful tool for reducing the incidence of athletes suffering

from OT (Hooper et al., 1997; Morgan et al., 1987a, 1988a, 1988b; Raglin, 2001).

The most well-documented and widely-used approach focuses on mood disturbance as

assessed by the POMS (McNair et al., 1971). This 65-item adjective checklist was

developed as a measure of typical and persistent mood reactions to current life

situations and provides a global or total mood disturbance score based on measures of

specific mood states. Specifically, the total mood disturbance score is calculated by

summing scores for the negative mood states of tension, depression, anger, fatigue and

confusion and then subtracting the score for vigour. Designed to assist with the

assessment of progress in psychotherapy and counselling in outpatients, McNair and

colleagues (1971) indicated that a secondary application could be in research settings

with normal populations (+18 years, with some high school education).

In a classic series of studies, Morgan and colleagues (1987a, 1988b) demonstrated that

increases in training load among swimmers were reliably associated with increases in

POMS mood disturbance scores, while decreases in training load were associated with

decreases in mood disturbance scores. These studies were conducted over a 10-year

time-frame and involved 400 competitive collegiate swimmers (200 female and 200

male). Results revealed that a dose response relationship existed between training load


Page | 29

and mood state, such that significant increases in training load were associated with

increases in mood disturbance. The earliest psychological changes noted on the POMS

occurring with OR were increases in fatigue and decreases in vigour. Changes in

tension, depression and anger appeared to follow with chronic OT. From their research,

five to 10% (20 to 40) of swimmers were diagnosed as suffering from training distress,

and 80% (16 to 32) of swimmers from this subgroup exhibited clinical depression.

Based on these findings, Morgan and colleagues (1987a, 1988b) concluded that the

interpretation of individual mood profiles may successfully predict the performance

decrements associated with OT. Thus, the POMS was accepted as an effective method

of monitoring the consequences of OT.

Subsequent studies have replicated these findings for swimmers and documented

similar responses to heavy training for many other sport activities including running,

cycling, canoeing, and basketball (e.g., Berglund & Sfstrm, 1994; Flynn et al., 1994;

Martin, Andersen, & Gates, 2000; Raglin, Eksten, & Garl, 1995; Rietjens et al., 2005).

Raglin and Morgan (1994) have also identified a subset of POMS items that they

believe are particularly sensitive to the effects of high intensity training. However, while

the majority of research to date has found mood disturbances to be consistently higher

in athletes showing signs of OR or OT (O'Connor, 1997), some exceptions have been

noted.

Hooper and colleagues (1997) suggested that based on previous research, OR athletes

may present with similar levels of tension, depression, anger, vigour, fatigue and

confusion as athletes who are intensely trained but not suffering from training distress.

Fourteen swimmers were subsequently monitored over a six-month training period. Of

this group, three swimmers were classified as suffering from training distress. The

researchers concluded that while the POMS appears to be useful for monitoring those


Page | 30

athletes predisposed to OR, it does not differentiate between athletes experiencing

training distress as opposed to those simply exhibiting the signs and symptoms

associated with intense training.

Furthermore, while the POMS has been the most frequently used psychological

inventory in OT research, some authors have disputed its validity. One common

criticism has been that the POMS is essentially a clinical screening instrument and was

not designed for athlete use, particularly not for diagnostic purposes. Therefore, it is

possible that a sport-specific mood instrument, such as the Training Distress Scale

(TDS) developed by Raglin and Morgan (1994) from the POMS scale items may be

more appropriate. In addition, the POMS restricts its focus to mood states. Depression

and other negative mood states such as tension can occur for reasons unrelated to OT,

and an exclusive focus on mood disturbance could therefore be problematic for accurate

diagnosis of athletes at risk of OT (Raglin & Wilson, 2000). Self-report measures that

supplement measures of mood disturbance with measures of other physiological states

might reduce this type of measurement error.

2.3.2 Behavioural Changes

A second approach to the monitoring of training distress via self-report involves the use

of behavioural symptom checklists. A variety of such checklists have been used, based

on observations of muscle soreness, general lethargy, insomnia, loss of appetite, and/or

susceptibility to minor illness during periods of high-intensity training (e.g., Fry et al.,

1994b; OConnor, 1997; Raglin & Wilson, 2000). Morgan and colleagues (1988) were

among the first to systematically monitor such parameters. While the primary focus of

their research was on mood disturbance following increased training, they also took a

number of physical symptom measures. Muscle soreness was measured with a seven

point categorical scale on a daily basis prior to training. An overall rating of muscle


Page | 31

soreness was obtained as well as ratings for the calf, thigh, forearm and shoulder.

Results revealed a significant increase in perceptions of muscle soreness within each

muscle group as well as an increase in overall muscle soreness.

Hooper and colleagues (1995) investigated a wide range of parameters during a 6-month

swimming study. The purpose was to determine which parameters could be used to

monitor OT and recovery. In addition to a range of biochemical markers, a battery of

well-being questions were included in a daily training log. Questions included quality of

sleep, fatigue, stress and muscle soreness and subjective ratings were measured on a

scale of 1-7. Body mass, early-morning HR, occurrence of illness, menstruation and

causes of stress were also recorded. Regression analysis revealed a battery of well-being

ratings which predicted OT scores, accounting for 76% of the variance. It was

concluded that self-reported ratings of well being may provide an efficient means of

monitoring both OT and recovery.

Similarly, the use of training-specific symptoms as a means of monitoring OR was

further investigated by Fry and colleagues (1992a, 1994b). Symptoms identified

included behavioural, psychological, and physical complaints. Fry and colleagues

(1994b) found that OT was accompanied by severe fatigue, immune system deficits,

mood disturbance, physical complaints, sleep difficulties, and reduced appetite. Mood

states moved toward baseline during recovery, but feelings of fatigue and immune

system deficits persisted throughout the study. It must be acknowledged that it is

entirely possible that these enduring feelings of fatigue are a consequence of factors

outside of an athletes sport participation.


Page | 32

2.3.3 Perceived Stress

Athletes who train with adequate rest and recovery periods still have other sources of

stress to cope with. In addition to the physiological responses to excessive overload

training, failure to cope with everyday, sport-specific, social and other environmental

stressors also contribute to the OT process (Tenenbaum et al., 2003b). It is entirely

possible for OTS to develop when a normally tolerable volume and intensity of training

is undertaken, but other stressors from the environment, such as work and private (i.e.

family) circumstances are present (Cohen, Kamarck, & Mermelstein, 1983; Kellmann,

2002; Rowbottom et al., 1998b). During periods of high extraneous stress (e.g.

educational, environmental, occupational, or social stress), training volumes and

intensities may need to be modified and scaled down; as together, the combination of

stressors may exceed the individuals capacity to adapt.

Indeed, high self-reported stress levels have been shown to be associated with both OT

(Hooper et al., 1995) and OR (Mackinnon et al., 1997). As such, a third approach to the

monitoring of training distress via self-report has focused on measures of perceived

stress. Rushall (1990) as well as Myers and Whelan (1998), argued that training-specific

stressors often combine with various sources of stress outside of sport to influence an

athletes mental and physical readiness to perform. Rushall (1990) further suggested

that it was particularly important to monitor perceived stress during periods of heavy

training, because of the potential for perceived stress to increase fatigue levels and, in

turn, decrease performance capabilities.

With the understanding that the cumulative nature of stress has the potential to be

detrimental to performance, Rushall (1990) developed a self-report inventory for

measuring stress tolerance in elite athletes called the Daily Analysis of Life Demands

(DALDA). Rushall recognised that athlete stressors originated from outside, as well as


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within the sporting environment. As such, to understand an athletes response to the

specific stress of training, Rushall perceived that it was necessary to measure all sources

of stress. The DALDA identifies 12 areas of life stressors and 42 symptoms of stress

(Rushall, 1990). The inventory is divided into two parts and results are kept in a log

book. Halson et al. (2002) documented predictable workload-related increases in

perceived stress among cyclists during a two-week period of high intensity training and

proposed that the DALDA questionnaire may be an effective and practical tool to

determine whether a reduction in performance is the result of the fatigue response to

acute training or from OR/ OT.

Kellmann and others (Kentt & Hassmn, 1998; Kellmann, 2002) have added

consideration of recovery processes to this approach and have conducted a number of

studies examining stress-recovery states (Kellmann, 2002). Kellmann and Gnther

(2000), for example, found significant changes in stress-recovery profiles of German

rowers during high-intensity training periods prior to the 1996 Olympics. Similar

findings were obtained for junior rowers preparing for the 1995 and 1998 World

Championships (Kellmann, Altenburg, Lormes, & Steinacker, 2001; Steinacker et al.,

2000). In order to assist with the identification of an athletes physical and mental

stress, as well as the extent of current recovery activities, Kellmann and Kallus (2001)

developed the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport). The

Recovery-Cue (Kellmann, Botterill, & Wilson, 1999) was subsequently developed in

addition to the RESTQ Sport to provide feedback regarding current stress and recovery

states, but also to increase an athletes knowledge and awareness of their stress and

recovery. Both of these measures have been shown to be practical and effective in the

assessment and monitoring of training stress and recovery (Kellman, Patrick, Botterill,

& Wilson, 2002; Steinacker et al., 2000).


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Part 3: Proposed Mechanisms of Overtraining

Although many of the symptoms of OT are similar to the resistance and exhaustion

stages of the Hans Seyles 1956 general adaptation syndrome (GAS), this model does

not clarify the exact mechanism of OTS. Attempts to understand the causes of OT have

approached the phenomenon from a number of different perspectives. These range from

initiating events and biological markers or indices of fatigue as discussed above;

nutritional imbalances and bodily responses to stressors; to hormonal perturbations,

changes in immune response and disturbances of mood state. While several theories

now exist, scientists acknowledge that the mechanisms of OT remain unknown.

However, there is consensus that it is most likely to result from a combination of: a)

inadequate recovery between training sessions, b) excessive amounts of high intensity

training, c) sudden increases in training loads, and d) additional training and non-

training stressors (Fry et al., 1991; Halson & Jeukendrup, 2004).

Lehmann, Foster, Dickhuth and Gastmann (1998) presented a figure that outlined

potential mechanisms underlying the genesis of OTS in endurance sport. The original

figure was revised and has been presented below as Figure 2.2 (Lehmann et al., 1999).

Based on the premise that OT develops as the result of a stress-recovery imbalance, the

diagram implies that performance decrements are the result of altered immune function,

peripheral fatigue, altered mood state and central fatigue. Altered reproductive function

is also believed to be involved. However, these outcomes of a stress-recovery imbalance

are only hypothesised to cause a performance decrement. Further research is needed to

confirm this model.


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3.1 Alterations to the endocrine axis

Although many hormonal indicators of OR and OT have been proposed, appreciation of

the exact mechanism behind the aetiology of OT has been difficult (Smith & Norris,

2000). It has been suggested that OT may result from a multitude of factors; including

an anabolic/catabolic imbalance (Aldercrentz et al., 1986), hormonal dysfunction of the

pituitary axis (Barron, Nokes, Levy, Smith, & Millar, 1985; Urhausen et al., 1998a), an

amino acid imbalance (Bailey, Davis, & Ahlborn, 1993; Newsholme, Parry-Billings,

McAndrew, & Budgett, 1991) or autonomic dysfunction (Lehmann et al., 1998). One

proposal was that overreaching is probably associated with insufficient metabolic

recovery, resulting in a decline in ATP levels, while acute OT or OTS may be

attributed to failure of the hypothalamus to cope with the total amount of stress

(Kuipers, 1998).

Figure 2.2: Selected mechanisms underlying the genesis of OTS in endurance sport

(Lehmann et al., 1999)


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Several investigators have focused on the role of the hypothalamus, activation of the

autonomic nervous system and the hypothalamic-pituitary-adrenal axis (HPA), as well

as the hypothalamic-pituitary-gonadal axis (HPG). Alteration of each of these endocrine

axes, may account for alterations in blood catecholamine, glucocorticoid, and

testosterone levels, which have been frequently associated with OTS. However, recent

developments suggest that activation of these pathways may be consequential rather

than causational. Further research is required to assess this proposal.

3.2 Metabolic hypothesis

Following periods of overload training, it has been shown that there is a period during

which homeostasis is restored through metabolic processes, enhancing the energetic

supply to skeletal muscles (Petibois, Cazorla, Poortmans, & Deleris, 2002). The length

of this period is dependent on the degree to which homeostasis was disrupted (Fry et al.,

1991).

Both physical activity and diet stimulate processes that, over time, alter the

morphologic composition and biochemical function of the bodyThe metabolic

stress of physical activity can be measured by substrate turnover and depletion,

cardiovascular response, hormonal perturbation, accumulation of metabolites, or

even the extent to which the synthesis and degradation of specific proteins are

altered, either acutely or by chronic excessive training. (Colye, 2000, p. 512S)

One popular view has been that OT is caused by alterations in the metabolic processes.

Seven main hypotheses involving metabolic processes or pathways have been presented

in relation to OT, with each one relating to a central parameter (i.e. carbohydrates,

branched-chain amino acids, glutamine, polyunsaturated fatty acids, leptin and

proteins). As with all other areas of OT research, there is mixed support for each of


Page | 37

these hypotheses and, while there appear to be valid links, there is also supporting

evidence as to why each hypothesis is unlikely to be the primary cause of OT as

illustrated in Table 2.4. While this table is very simplistic and only offers a brief glance

at each of these proposed hypotheses and research areas, it provides a general

background to current research trends.

The ability to distinguish more clearly between previously proposed mechanisms may

be enhanced by recent advances in technology. Analytical equipment now exists that

provides researchers with a global, sensitive, and highly reproducible physiochemical

analytical technique that identifies structural moieties of bio-molecules on the basis of

their infra-red absorption (Petibois, Cazorla, & Deleris, 2000). Fourier-transform infra-

red (FT-IR) spectrometry provides researchers with the ability to analyse 50L capillary

blood samples and obtain a complete biochemical breakdown of the whole sample.

Using this technology, recent studies have shown that OT could result from successive

and cumulative alterations in metabolism that become chronic during prolonged periods

of endurance training (Petibois et al., 2002, 2003a, 2003b).

Petibois and colleagues (2000) described the process of OT as successive alterations in

exercise metabolism that shift from the main energetic stores of exercise (carbohydrates

and lipids) towards molecular pools (proteins) normally not used for the energetic

supply of skeletal muscles. These stepwise progressions are illustrated in Table 2.5. As

such, a general biochemical model of the OT process may soon be proposed which

includes most of the previously identified metabolic pathways.

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Table 2.4: A summary of proposed metabolic hypotheses

Hypothesis Presumptions However

Carbohydrate hypothesis

(Achten et al., 2003; Manetta et

al., 2002)

Fatigue may be induced by a slight transient hypoglycaemia, due to

hepatic and/or muscle glycogen store depletion, and/or failure in

glycogenolytic metabolic flux

It has been suggested that long-term glycogen depletion would lead to

an increased BCAA oxidation which is more likely to be responsible

for a central fatigue process and subsequent negative mood states

BCAA hypothesis

(Gastmann & Lehmann, 1998)

Increased free fatty acid transport to skeletal muscles induced a

higher utilisation of albumin transport capacities. This in turn leads to

increased release of free tryptophan. Increased cerebral tryptophan is

converted into serotonin. Instrumental in modulation of the body

Although an influx in serotonin does not appear to be a sufficient

inducer of central fatigue to lead to OT in endurance athletes, it may

increase athlete susceptibility. Results concerning this hypothesis are

inconclusive and require more controlled experimental research.

Glutamine hypothesis

(Boelens et al., 2001)

One of the most abundant amino acids in the body, it is metabolised

by immune cells. Proliferation depends on glutaminolysis, suggesting

that a decrease in blood glutamine concentration may be at least

partially responsible for immune function deficiency or impairment.

Immunosuppression has been observed in OT athletes without

decreases in glutamine concentrations and in the absence of URTIs.

Polyunsaturated fatty acid

hypothesis

(Calder & Newsholme, 1992)

Given the recurrent occurrence of immune suppression in overtrained

athletes, this alt

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