ArticlePDF Available

Investigation of the Profile of Mood State (POMS) questionnaire as an indicator of Overtraining Syndrome (OTS) in a group of endurance athletes


Abstract and Figures

The Overtraining Syndrome is largely a diagnosis of exclusion. The aim of this study was to investigate the compact Profile of Mood State (POMS) questionnaire as an early and accurate indicator for the diagnosis of OTS and the reliability of such findings between a group of athletes diagnosed with OTS, in comparison with a non-OTS (NOTS) group. The study population included 10 endurance athletes who completed the compact version of the POMS test which is based on 65 questions using a 4-point adjective rating scale which measure 6 identifiable moods of affect states: tension-anxiety; depression-dejection; anger-hostility; vigour-activity; fatigue-inertia; and confusion-bewilderment. Anger, vigor and fatigue all reflected p values < 0.0001, thus showing reliability in predicting OTS. The study showed significant differences in mood states between the OTS and the NOTS group. Only tension was similar in both groups. The POMS test was found to be a promising tool in the early diagnosis of OTS.
Content may be subject to copyright.
Investigation of the Profile of Mood State (POMS) questionnaire as an indicator of
Overtraining Syndrome (OTS) in a group of endurance athletes
1Section Sports Medicine, School of Medicine, Faculty of Health Sciences, University of
Pretoria, Pretoria, South Africa
2Department of Biokinetics, Sport and Leisure Sciences, University of Pretoria
3Department of Human Physiology, School of Medicine, Faculty of Health Sciences,
University of Pretoria, Pretoria, South Africa
Corresponding author:
Mrs C.C. Grant
Section Sports Medicine
Faculty of Health Sciences
University of Pretoria
Pretoria, South Africa
Running head : Profile of Mood State questionnaire as an indicator of Overtraining
The Overtraining Syndrome is largely a diagnosis of exclusion. The aim of this study was to
investigate the compact Profile of Mood State (POMS) questionnaire as an early and accurate
indicator for the diagnosis of OTS and the reliability of such findings between a group of
athletes diagnosed with OTS, in comparison with a non-OTS (NOTS) group. The study
population included 10 endurance athletes who completed the compact version of the POMS
test which is based on 65 questions using a 4-point adjective rating scale which measure 6
identifiable moods of affect states: tension-anxiety; depression-dejection; anger-hostility;
vigour-activity; fatigue-inertia; and confusion-bewilderment. Anger, vigor and fatigue all
reflected p values < 0.0001, thus showing reliability in predicting OTS. The study showed
significant differences in mood states between the OTS and the NOTS group. Only tension
was similar in both groups. The POMS test was found to be a promising tool in the early
diagnosis of OTS.
Key words: Overtraining Syndrome, diagnosis, Profile of Mood State questionnaire.
The Olympic motto citius, altius, fortius (faster, higher, stronger) epitomizes the goal of
athletic training (Robson-Ansley, Lakier, Smith, 2006). As athletes strive to improve their
performance, inevitably their training load increases (Robson-Ansley et al., 2006).
Frequently, their training strategies are successful and their performance improves. However,
when prolonged excessive training stresses are applied concurrent with inadequate recovery,
performance decrements and chronic maladaptations occur. Known as the Overtraining
Syndrome (OTS), this complex condition afflicts a large percentage of athletes at least once
during their careers (Armstrong & Van Heest, 2002). Armstrong and Van Heest (2002)
proposed that OTS and MD (major depression) have similar aetiologies. Overload refers to a
planned, systematic, progressive increase in training stimuli that is required for improvements
in strength, power and endurance. Over-reaching refers to training that involves a brief period
of overload, with inadequate recovery that exceeds the athlete’s adaptive capacity.
Overtraining exceeds overreaching and results in frank physiological maladaptations and
chronically reduced exercise performance (Armstrong & Van Heest, 2002).
Signs and symptoms of OTS
Fry, Morton & Keast (1991) have listed over 90 signs and symptoms in their 1991 review of
OTS. Selected signs and symptoms as described in the published review article by Robson-
Ansley et al. (2006), are the following: decreased physical performance, general fatigue,
malaise, loss of vigour, insomnia, change in appetite and mood, loss of bodyweight, loss of
motivation, lack of mental concentration and feelings of depression.
The above symptoms may also be associated with the diagnosis of clinical depression and
could be the underlying cause of OTS and the use of antidepressants to treat OTS may be
recommended (Armstrong & Van Heest, 2002). It is, therefore, ironic that whilst physical
activity may play an important role in the management of mild to moderate depression,
excessive physical activity may lead to overtraining and generate psychological symptoms
that mimic depression (Paluska & Schwenk, 2000).
Tools for diagnosing OTS
OTS is largely a diagnosis of exclusion (Nederhof , Zwerver & Brink, 2008). Organic
diseases that may mimic the symptoms of OTS must be excluded first (Urhausen &
Kindermann, 2002). These diseases include hypothyroidism, renal failure, major depression,
anaemia, nutritional deficiencies, connective tissue diseases, diabetes mellitus, drugs,
paroxysmal atrial tachycardia, muscular dystrophies, stress, Cushing’s disease and tissue
trauma. Tools to diagnose OTS may be used at rest or during exercise. There is no gold
standard test to diagnose OTS, thus early and unequivocal recognition of OTS is virtually
impossible because the only certain sign is a plateau or decrease in performance during
competition and training (Armstrong & Van Heest, 2002).
Tools for diagnosing OTS at rest
a) Heart Rate (Urhausen & Kindermann, 2002).
b) Mood State and Subjective Complaints, for example, the POMS questionnaire (The POMS
questionnaire assesses tension, depression, anger, vigour, fatigue and confusion (McNair,
Lorr & Droppelman, 1971). The physical demands of overtraining are not the only elements
in the development of OTS (Armstrong & Van Heest, 2002). A complex set of psychological
factors are important in the development of OTS, including excessive expectations from a
coach and family, competitive stress, personality structure, social environment, relations with
family and friends, monotony in training, personal and emotional problems, and school or
work related demands (Armstrong & Van Heest, 2002)).
c) Blood tests including enzyme activities and metabolic markers, for example, Creatinine
kinase (CK), urea, uric acid and ammonia (Rietjens, Kuipers, Adam, Saris, van Breda, van
Hamont & Keizer, 2005)
d) Hormone testing, for example, catecholamines and testosterone, including the cortisol ratio
(Brukner & Khan, 2006)
e) Immunological Parameters such as Glutamine (Urhausen & Kindermann, 2002)
Materials and Methods
Patients included in the study were endurance athletes diagnosed with OTS by a sports
medicine physician. The diagnosis was based on patient history, ruling out other diseases, and
the presence of some OTS symptoms. These symptoms included: low-grade psychological
and psychosomatic symptoms (e.g. anger, fatigue, tension, loss of appetite); short-term
sleeping problems; muscle fatigue; immunologic or hormonal disturbances such as menstrual
irregularities; more severe symptoms such as depression, severe long-term insomnia, long-
term muscle soreness, or abnormal sense perceptions; a feeling of unwillingness to train and
of inability to go on training; and, most importantly, decreased level of performance. This
study was conducted over a specific time during the recovery period after OTS was
diagnosed. The results were statistically evaluated to develop a diagnostic tool for OTS.
The primary aim of the study was thus to determine if there was a statistical difference in the
results obtained from the POMS questionnaire completed by the OTS group athletes and
those obtained from the NOTS athletes (i.e. the athletes without any signs and symptoms of
Study Population
The study population included 10 endurance athletes who were diagnosed with OTS by
specific criteria mentioned above, and 19 athletes without signs and symptoms of OTS. The
athletes were from the High Performance Centre (UP) and various athletic clubs around
A formal Protocol Application was proposed to the Faculty of Health Sciences Research
Ethics Committee at the University of Pretoria, and accepted. Participation was voluntary and
informed consent was obtained prior to participation in the project. To standardize the
conditions, participants were asked to refrain from exercise, alcohol and caffeine ingestion 24
hours prior to the trial. Pre-printed questionnaires of the POMS test were given to all
participants to complete. This was a compact version of the POMS, the POMS brief which is
based on 65 questions using a 4-point adjective rating scale which measures 6 identifiable
moods of affect states. Consultation with potential participants took place over a period of 3
Study exclusion criteria included:
Pace makers
Renal failure
Diabetes Mellitus
Organic pathology or physical injury resulting in compromised exercise ability
Ischaemic heart disease
Nutritional deficiencies
Cushing’s disease
Muscular dystrophies
Tissue trauma
Demographic data is represented in Table 1. The mean age of the participants ranges between
27 and 29 years of age. The mean BMI was below 25.
Table 1
Experimental Data
Differences of the statistical data were plotted in the six different variables as shown in Table
2 and Table 3.
Table 2
Table 3
The total number of participants was 29. Vigour had the highest score and was inversely
proportional to anger.
In Table 3, fatigue had the highest score in the OTS group, which is one of the presenting
signs of OTS, while in the NOTS group, vigour showed a peak which correlates with a better
outcome in competition. The other emotions - tension, depression, anger, vigour and
confusion - had similar scores in the OTS group, whereas in the NOTS group, tension had a
higher value than depression, anger, fatigue and confusion.
Whilst in Figure 1 the NOTS group of athletes show a typical iceberg profile with a peak in
vigour, the OTS group have a p-value of <0.0001 in anger, vigour and fatigue. This, makes
these variables significant when compared to the NOTS group of athletes.
Figure 1
Also of significance is that anger and fatigue have a negative correlation to vigour and
positively related to depression (Table 4).
Table 4
The values for tension in both groups were closely related and would, therefore, be a poor
predictor of athletic performance (Table 5).
Table 5
In the present study, the POMS questionnaire was used to compare the profiles of the OTS
group (diagnosed with OTS by specific criteria set by a multi-disciplinary team) with the
NOTS (normal athletes). Few studies have focused on OTS versus normal athletes (NOTS),
hence the need for a study of this nature.
An impaired mood state and subjective complaints are consistently described as sensitive and
early markers of OTS (Prapavessis, 2000; Armstrong & Van Heest, 2002). The most fruitful
measurements have been of mood, evaluated by the POMS test (Armstrong & Van Heest,
2002). The deterioration in mood state usually starts well before the definitive drop in
performance and parallels the increase in training load. The subjective complaints are
dominated by a pronounced feeling of muscular soreness (‘heavy legs’ in runners, tri-athletes
and cyclists), which usually occurs during low exercise intensities and daily activities. Sleep
disorders may also be an early indicator sign of OTS (Armstrong & Van Heest, 2002).
The ability to produce and maintain appropriate emotional feelings before competition is
universally recognized by athletes and coaches as one of the most important factors
contributing to athletic performance (Prapavessis, 2000).
The conceptual approach, primarily through Morgan’s (1987) Mental Health Model, proposes
that positive mental health (i.e. emotional) and successful athletic performance is strongly
correlated. Athletes who are less anxious, angry, depressed, confused and fatigued, and more
rigorous, will be more successful than athletes who exhibit the opposite profile, as assessed
by POMS (Mc Nair, D.M., Lorr, M. & Droppelman LF, 1992; Prapavessis, 2000). Most of
the studies have concentrated on this aspect.
This positive profile of mood states has been termed the iceberg profile by Morgan (Morgan,
1987) since five negative mood states fall below the population norms and the one positive
mood lies above it (Prapavessis, 2000). The ease with which changes in mood state may be
measured as compared to the majority of physiological markers previously used, encourages
monitoring of athletes (Pierce, 2002).
The compact POMS is based on 30 questions, using a 4-point adjective rating scale which
measures 6 identifiable moods of affect states: tension-anxiety; depression-dejection; anger-
hostility; vigour-activity; fatigue-inertia; and confusion-bewilderment.
Rietjens, Kuipers and Adam (2005) found that cognitive function is the first and most
sensitive parameter for detecting overreaching and that reaction time values (indicative of
cognitive functioning), combined with POMS (indicative of mood state) and rate of perceived
exertion (useful for calculating the subjective training load), enables the athlete and his coach
to prevent over reaching and over training.
There appears to be individual variability in the threshold of training leading to OTS. Daily
monitoring of self-analysis measures, such as the athlete’s perception of training adaptation,
stress levels, fatigue, and quality of sleep and muscle soreness, may be effective in
identifying susceptible athletes before the appearance of other symptoms (MacKinnon, 2000).
Once OTS has set in, however, a modified POMS questionnaire can be used to diagnose the
condition and changes made to the training schedule, with a period of recovery.
Morgan (Morgan, Brown, Raglin, O’Connor & Ellickson, 1987) used the POMS
questionnaire pre-competition to predict outcome of participants in sports. The rearchers used
the POMS questionnaire for athletes already displaying symptoms of OTS to assess whether
it is reliable in diagnosing OTS, as compared to NOTS athletes. Some studies (Morgan,
1987) found a typical ‘iceberg’ profile with a peak in vigour in those athletes who were
predicted to have a positive outcome in competition. As seen in Figure 1, the NOTS groups
of athletes have a typical ‘iceberg’ profile with a peak in vigour.
In contrast, the OTS athletes have a peak in fatigue which is one of the presenting symptoms
of OTS and a dip in vigour - a typically inverse ‘iceberg’ profile. This correlates with poorer
outcome in competition.
The values for tension of both groups were the most closely related and would, therefore, be a
poor prediction of athletic performance. Since these are not professional athletes, other
factors such as work, socio-economic circumstances and family stressors could have
contributed to this finding.
Although depression had a higher score in OTS, this could be related to the individual’s
personal bio-psychosocial factors that could affect his mood state at the time and would affect
his sport performance.
Anger, vigour and fatigue had p-values of <0.0001 which makes them significant in
comparing the two groups. This may represent the first objective calculated variable available
to distinguish OTS and NOTS athletes. Also of interest is that anger and fatigue have a
negative relation to vigour, as seen on Table 3, giving a p-value of <0.001 and positively
related to depression. This study, using the POMS questionnaire to diagnose OTS, had
similar results to other studies (Fry, Morton & Keast, 1991; Fry, Grove, Morton, Zeroni,
Gaudieri & Keast, 1994; Prapavessis, 2000; Urhausen & Kindermann, 2002; Pierce, 2002;
Filiare, Legrand, Lac & Pequignot, 2004).
Kentta, Hassmen and Raglin (2001) found that the incidence of OTS was higher in individual
rather that team sports, and this could also be the reason for the greater difference in values
between OTS and NOTS considering that the subjects were athletes.
In his article “Markers of Excessive Exercise” Mc Kenzie (1999) noted that the order of
decrement in OTS is psychological status, medical condition then performance. It therefore
makes sense to use the POMS to diagnose OTS before medical problems and performance
are affected.
The modified POMS questionnaire maybe used to detect early signs of OTS in susceptible
individuals. Its use is not restricted to athletes, but is also applicable to subjects who are
expected to carry out other physically strenuous activities, such as military personnel.
A study with a larger number of participants would have greater reliability and credibility.
Repetition of the POMS questionnaire in OTS after a recovery period, with changes in the
reading, would substantiate the findings. A list of culturally appropriate adjectives to
substitute for POMS items that might be misunderstood would also be of value when using
this tool in different culture and language populations (Prapavessis, 2000).
Armstrong, L.E. & Van Heest, J.L. (2002). The Unknown Mechanism of the Over Training
Syndrome. Sports Medicine, 32 (3), 185 – 209.
Brukner, P. & Khan, K. (2006). Clinical Sports Medicine (3rd ed.). Sydney: Mc Graw-Hill,
Filiare, E., Legrand, B., Lac, G. & Pequignot, J.M. (2004). Training of Elite Cyclists: effect
on mood state and selected hormonal responses. Journal of Sports Sciences, 22(11-12), 1025-
Fry, R.W., Morton, A.R. & Keast, D. (1991). Overtraining in Athletes: An Update. Sports
Medicine, 12(1), 32-65(Part 1) and (Part 2).
Fry, W., Grove, J.R., Morton, A.R., Zeroni, P.M., Gaudieri, S. & Keast, D. (1994).
Psychological and Immunological Correlates of Acute Overtraining. British Journal of Sports
Medicine, 28(4), 241-6.
Kentta, G., Hassmen, P. & Raglin, J.S. (2001). Training Practices and Overtraining
Synfdrome in Swedish Age Group Athletes. International Journal of Sports Medicine, 22(6),
MacKinnon, L.T. (2000). Overtraining Effects on Immunity and Performance in Athletes.
Immunology and Cell Biology, 78, 502-9.
Mc Nair, D.M., Lorr, M. & Droppelman LF. (1992). POMS: Profile of Mood States Manual.
Toronto: Multi Health Systems Inc.
Morgan, W.P., Brown, D.R., Raglin, J.S., O’Connor, P.J., Ellickson, K.A. (1987).
Psychological monitoring of overtraining and staleness. British Journal of Sports Medicine,
21(3): 107-14.
Nederhof, E., Zwerver, J., Brink, M., Meeusen, R., Lemmink, K. (2008). Different
Diagnostic Tools in Nonfunctional Overreaching. International Journal of Sports Medicine,
29(7), 590-7.
Paluska, S.A. & Schwenk, T.L. (2000). Physical Activity and Mental Health Current
Concepts. Sports Medicine, 29(3), 167-30.
Pierce, E.F. (2002). Relationship between Training Volume and Mood States in Competitive
Swimmers during a 24 week season. Perceptual and Motor Skills, 94 (3 Pt 1), 1009-12.
Prapavessis, H. (2000). The POMS and Sports performance: A Review. Journal of Applied
Sport Psychology, 12(1), 34-48.
Rietjens, G.J.W.M., Kuipers, H., Adam, J.J., Saris, W.H.M., van Breda, E., van Hamont, D.,
Keizer, H.A. (2005). Physiological, Biochemical and Psychological Markers of Strenuous
Training Induced Fatigue. International Journal of Sports Medicine, 26(1/02), 16 - 26.
Robson-Ansley, P.J., Smith, L.L.. (2006). Causes of Extreme Fatigue in Underperforming
Athletes-a synthesis of recent hypothesis and reviews. South African Journal of Sports
Medicine, 18(4), 108-14.
Urhausen, A. & Kindermann, W. (2002). Diagnosis Of Overtraining. What tools do we have?
Sports Medicine, 32(2), 95-102.
Table 1: Demographic Data
OTS mean
Weight (Kg)
Height (cm)
Age (Years)
Table 2: Comparative values for different variables
Total Means
Standard Variable
Table 3: Comparative values for OTS and NOTS variables in Mean Values, Standard
Deviation and Coefficient of the Variations
Variable Means Standard Deviations
Coefficients of
Table 4: Pearson Correlation Coefficients for different Variables
Tension P
Depression P
Anger P
Vigour P
Fatigue P
Confusion P
Table 5: The discriminant coefficients of the linear discriminant functions
tension p=0.0532
anger p<0.0001
fatigue p<0.0001
Figure 1: Descriptive Analysis of Mean Values between OTS and NOTS groups
... As displayed in Table 1, 19 studies examined athletes from different sports, 1,2,[4][5][6][7][8][9]12,13,[15][16][17]20,24,29,36,37,[43][44][45]53,54,58,64,66,68,72 while 9 studies focused on 1 single sport. Two studies did not disclose the type of sport played. ...
... In total, 952 subjects were examined including 328 athletes diagnosed with OTS and 624 healthy control subjects. In 24 studies, the athletes were already previously affected by OTS, 2,[4][5][6][7][8][9]12,[15][16][17]20,24,29,30,34,36,37,[42][43][44][45]47,53,54,[56][57][58]64,65,68,72 while in 6 studies, OTS developed during the study. 1,27,60,61,66,71 A total of 7 studies were uncontrolled: 2 studies did not have any control group, 4,24 and 5 studies were case-reports with only 1 subject and no control. ...
... 47,57 Four studies did not specify participants' sex. 29,43,44,58,65 The duration of performance decrement was at least 3 weeks in all the studies included. ...
Full-text available
Context Overtraining syndrome (OTS) is a condition characterized by a long-term performance decrement, which occurs after a persisting imbalance between training-related and nontraining-related load and recovery. Because of the lack of a gold standard diagnostic test, OTS remains a diagnosis of exclusion. Objective To systematically review and map biomarkers and tools reported in the literature as potentially diagnostic for OTS. Data Sources PubMed, Web of Science, and SPORTDiscus were searched from database inception to February 4, 2021, and results screened for eligibility. Backward and forward citation tracking on eligible records were used to complement results of database searching. Study Selection Studies including athletes with a likely OTS diagnosis, as defined by the European College of Sport Science and the American College of Sports Medicine, and reporting at least 1 biomarker or tool potentially diagnostic for OTS were deemed eligible. Study Design Scoping review following the guidelines of the Joanna Briggs Institute and PRISMA Extension for Scoping Reviews (PRISMA-ScR). Level of Evidence Level 4. Data Extraction Athletes’ population, criteria used to diagnose OTS, potentially diagnostic biomarkers and tools, as well as miscellaneous study characteristics were extracted. Results The search yielded 5561 results, of which 39 met the eligibility criteria. Three diagnostic scores, namely the EROS-CLINICAL, EROS-SIMPLIFIED, and EROS-COMPLETE scores (EROS = Endocrine and Metabolic Responses on Overtraining Syndrome study), were identified. Additionally, basal hormone, neurotransmitter and other metabolite levels, hormonal responses to stimuli, psychological questionnaires, exercise tests, heart rate variability, electroencephalography, immunological and redox parameters, muscle structure, and body composition were reported as potentially diagnostic for OTS. Conclusion Specific hormones, neurotransmitters, and metabolites, as well as psychological, electrocardiographic, electroencephalographic, and immunological patterns were identified as potentially diagnostic for OTS, reflecting its multisystemic nature. As exemplified by the EROS scores, combinations of these variables may be required to diagnose OTS. These scores must now be validated in larger samples and within female athletes.
... In elite athletes assessments of mood and mental states are used to detect functional and non-functional overreaching [25]. Especially anger, vigor and fatigue are reliable indicators of overtraining [26] as those mood states correlate with training volume [27]. In TBT and STAR mood and mental states remained relatively stable over the intervention period, although there was a progression of exercise intensity and duration. ...
Full-text available
The aim was to assess factor structure of player-reported fatigue and quantify within-subjects association between changes in training load measures and next day player-reported fatigue at different time points of an elite football season. Using longitudinal research design, twenty-four professional footballers, mean (SD) age of 25.7 (3.4) years, were monitored during their competitive season, including pre-season. Player-reported fatigue data and session ratings of perceived exertion (session-RPE) were collected via a mobile application. Player’s Heart rate (HR) and global positioning system (GPS) data were collected daily for each player in field sessions. Principal component analysis (PCA) indicated three components with Eigenvalues above 1.0; “soreness”, “mood, and “hydration”. Within-player correlations between training load values and next day player-reported fatigue values were trivial to moderate (r ≈ −0.42 to −0.04). In-season we observed large correlations between Total Distance (TD) and PlayerLoad with Soreness (r = −0.55, 95% CI: −0.62 to −0.46; r = −.054, 95% CI: −0.62 to −0.46), but during pre-season, correlations were small (r = −0.15, 95% CI: −0.28 to −0.01; r = −0.13, 95% CI: −0.26 to 0.01). The HR TRIMP, TD and session-RPE measures each showed trivial to moderate correlations (r ≈ −0.41 to −0.08) with next day “mood”. Our in-house player-reported fatigue questionnaire was sensitive to the multi-dimensional nature of fatigue, identifying physiological (soreness), psychological (mood and stress) and nutritional (hydration and nutrition) components. We found the in-season correlations with training load to be greater than previously reported in the literature, specifically with next day player-reported “soreness”. Nevertheless, the correlations between the items of our scale and pre-season training load were small.
Conference Paper
Problemstellung: Ein Trainingsprozess mit größtmöglichen Effekten sollte immer auf die individuellen Belastungs- und Erholungsphasen abgestimmt sein. Im Blickfeld der Forschung steht daher die Verwendung eines Trainingsprogrammes basierend auf der Messung der Herzfrequenzvariabilität (HRV) (Hautala et al., 2009; Friden, et al., 2003). Ziel dieser Studie ist der Vergleich der Wirkungsweise gegenüber einem strukturierten Trai-ningsplan auf Ausdauerleistung, Stimmungslage und Befindlichkeit. Methoden: Für die Studie wurden 20 gesunde und moderat trainierte Freizeitläufer (10m/10w; 41,5 ± 8,6 Jahre) rekrutiert. Die Probanden wurden randomisiert einem adaptiven, HRV-basierten Training (STAR) mit wöchentlicher Zielvorgabe oder einem zeitlich strukturierten Training (TBT) zugeteilt. Vor und nach der Intervention (12 Wochen) wurde ein Stufentest mit Spirometrie zur Bestimmung der maximalen Sauerstoffauf-nahme (VO2max) und Geschwindigkeit (vmax) durchgeführt sowie die Stimmung und Befindlichkeit erfragt (BFS). Die Daten wurden per zweifaktorieller ANOVA für Mess-wiederholungsdesigns analysiert. Ergebnisse: Zwischen der STAR- und der TBT-Gruppe ergaben sich bezüglich der Veränderun-gen des Gewichts, Körperfetts und Blutdrucks keine Unterschiede. Stimmungs- und Befindlichkeitsveränderungen wurden nicht beobachtet. Eine gleichermaßen signifi-kante Verbesserung zeigte sich u.a. bei der VO2max (STAR: 43,0 ± 8,3 auf 46,1 ± 9,0, p<0,001; TBT: 43,2 ± 4,8 auf 46,7 ± 4,7, p<0,001) und der Zunahme der vmax (STAR: 0,74 + 0,39 km.h-1, p<0,001;TBT: 0,81 + 0,40 km.h-1 p<0,001). Diskussion und Schlussfolgerung: Die Ergebnisse der Studie deuten darauf hin, dass das Training der Gruppen HRV und TBT ähnliche Auswirkungen auf die Körperzusammensetzung und die Ausdauer-leistungs-fähigkeit hat. Schlussfolgernd bietet das HRV- und computergestützte Trai-ning unter Berücksichtigung der individuellen Bedürfnisse eine Alternative für die täg-liche Periodisierung der Ausdauerleistungsfähigkeit gegenüber einem zeitlich festge-legten Trainingsplan.
Full-text available
The underperformance syndrome (UPS), previously known as the overtraining syndrome (OTS), has been defined as a persistent decrement in athletic performance capacity despite 2 weeks of relative rest. Clinical research has suggested that cytokines play a key role in fatigue in disease and chronic fatigue syndrome. Furthermore, it has recently been demonstrated that exogenous administration of interleukin-6 (IL-6) increases the sensation of fatigue during exercise. In light of current cytokine and chronic fatigue syndrome research, this article reviews and updates the cytokine theories that attempt to explain the aetiology of the debilitating fatigue experienced in OTS/UPS. Initially, it was proposed that UPS may be caused by excessive cytokine release during and following exercise, causing a chronic inflammatory state and ‘cytokine sickness'. More recently, the hypothesis was extended and it was proposed that time-dependent sensitisation could provide a model through which the aetiology of UPS may be explained. According to this model, the principal abnormal factor in UPS is an intolerance/heightened sensitivity to IL-6 during exercise. South African Journal of Sports Medicine Vol. 18 (4) 2006: pp. 108-114
Full-text available
The general purpose of this paper is to critically review the literature on precom-petitive mood states (using the POMS) and sport performance. Specifically, important interpretative, conceptual, and methodological issues are examined to provide direction for future research. A position is taken that the Mental Health Model (iceberg profile) may not be the most suitable framework for understanding how precompetitive mood states are related to sport performance. A promising alternative approach is Hanin's Individual Zone of Optimal Function (IZOF) model.
Full-text available
Clinical Sports Medicine has been fully updated from the popular 2nd edition (2000). It is even more practical, now superbly illustrated, easy-to-read and packed with substantially updated and new material. There are samples of several chapters online including the whole "Pain in the Achilles region" chapter. This book describes a completely symptom-oriented approach to treating clinical problems.
Full-text available
It is widely agreed that overtraining should be employed in order to achieve peak performance but it is also recognised that overtraining can actually produce decrements in performance. The challenge appears to be one of monitoring stress indicators in the athlete in order to titrate the training stimulus and prevent the onset of staleness. The present paper summarises a ten-year research effort in which the mood states of competitive swimmers have been monitored at intervals ranging from 2-4 weeks during individual seasons for the period 1975-1986. The training cycle has always involved the indoor season which extends from September to March and the athletes who served as subjects were 200 female and 200 male competitive swimmers. The results indicate that mood state disturbances increased in a dose-response manner as the training stimulus increased and that these mood disturbances fell to baseline levels with reduction of the training load. Whilst these results have been obtained in a realistic setting devoid of experimental manipulation, it is apparent that monitoring of mood state provides a potential method of preventing staleness.
Full-text available
Five men undertook two intensive interval training sessions per day for 10 days, followed by 5 days of active recovery. Subjects supplied a venous blood sample and completed a mood-state questionnaire on days 1, 6, 11 and 16 of the study. Performance capabilities were assessed on days 1, 11 and 16 using a timed treadmill test to exhaustion at 18 kmh-1 and 1% grade. These individuals became acutely overtrained as indicated by significant reductions in running performance from day 1 to day 11. The overtrained state 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.
When prolonged, excessive training stresses are applied concurrent with inadequate recovery, performance decrements and chronic maladaptations occur. Known as the overtraining syndrome (OTS), this complex condition afflicts a large percentage of athletes at least once during their careers. There is no objective biomarker for OTS and the underlying mechanism is unknown. However, it is not widely recognised that OTS and clinical depression [e.g. major depression (MD)] involve remarkably similar signs and symptoms, brain structures, neurotransmitters, endocrine pathways and immune responses. We propose that OTS and MD have similar aetiologies. Our examination of numerous shared characteristics offers insights into the mechanism of OTS and encourages testable experimental hypotheses. Novel recommendations are proposed for the treatment of overtrained athletes with antidepressant medications, and guidelines are provided for psychological counselling.
Overtraining is a process of excessive exercise training in high-performance athletes that may lead to overtraining syndrome. Overtraining syndrome is a neuroendocrine disorder characterized by poor performance in competition, inability to maintain training loads, persistent fatigue, reduced catecholamine excretion, frequent illness, disturbed sleep and alterations in mood state. Although high-performance athletes are generally not clinically immune deficient, there is evidence that several immune parameters are suppressed during prolonged periods of intense exercise training. These include decreases in neutrophil function, serum and salivary immunoglobulin concentrations and natural killer cell number and possibly cytotoxic activity in peripheral blood. Moreover, the incidence of symptoms of upper respiratory tract infection increases during periods of endurance training. However, all of these changes appear to result from prolonged periods of intense exercise training, rather than from the effects of overtraining syndrome itself. At present, there is no single objective marker to identify overtraining syndrome. It is best identified by a combination of markers, such as decreases in urinary norepinephrine output, maximal heart rate and blood lactate levels, impaired sport performance and work output at 110% of individual anaerobic threshold, and daily self-analysis by the athlete (e.g. high fatigue and stress ratings). The mechanisms underlying overtraining syndrome have not been clearly identified, but are likely to involve autonomic dysfunction and possibly increased cytokine production resulting from the physical stress of intense daily training with inadequate recovery.
Overtraining appears to be caused by too much high intensity training and/or too little regeneration (recovery) time often combined with other training and nontraining stressors. There are a multitude of symptoms of overtraining, the expression of which vary depending upon the athlete's physical and physiological makeup, type of exercise undertaken and other factors. The aetiology of overtraining may therefore be different in different people suggesting the need to be aware of a wide variety of parameters as markers of overtraining. At present there is no one single diagnostic test that can define overtraining. The recognition of overtraining requires the identification of stress indicators which do not return to baseline following a period of regeneration. Possible indicators include an imbalance of the neuroendocrine system, suppression of the immune system, indicators of muscle damage, depressed muscle glycogen reserves, deteriorating aerobic, ventilatory and cardiac efficiency, a depressed psychological profile, and poor performance in sport specific tests, e.g. time trials. Screening for changes in parameters indicative of overtraining needs to be a routine component of the training programme and must be incorporated into the programme in such a way that the short term fatigue associated with overload training is not confused with the chronic fatigue characteristic of overtraining. An in-depth knowledge of periodisation of training theory may be necessary to promote optimal performance improvements, prevent overtraining, and develop a system for incorporating a screening system into the training programme. Screening for overtraining and performance improvements must occur at the culmination of regeneration periods.
Heavy training in combination with inadequate recovery actions can result in the overtraining/staleness syndrome and burnout. Even young and aspiring elite athletes develop staleness. The aim was therefore to determine the incidence and nature of staleness, and its association with training behavior and psychosocial stressors in young elite athletes. A sample of 272 individuals from 16 sports completed questionnaires on training, staleness, and psychosocial stress and 37% reported being stale at least once. The incidence rate was higher for individual sports (48%) compared with team (30%) and less physically demanding sports (18%). Stale athletes reported greater perceptual changes and negatively elevated mood scores in comparison to healthy athletes. Staleness was distinguished from burnout on the basis of motivational consequences; 41 % of the athletes lost their motivation for training, which in turn indicates a state of burnout. Further, 35 % of the athletes reported low satisfaction with time spent on important relationships, 29% rated the relationship with their coach as ranging from very, very bad to only moderately good. The results indicate that staleness is a widespread problem among young athletes in a variety of sports, and is not solely related to physical training, but also to non-training stressors.