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      Development and Validity of the Rating-of-Fatigue Scale

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          Abstract

          Objective

          The purpose of these experiments was to develop a rating-of-fatigue (ROF) scale capable of tracking the intensity of perceived fatigue in a variety of contexts.

          Methods

          Four experiments were carried out. The first provided the evidential basis for the construction of the ROF scale. The second tested the face validity of the ROF, and the third tested the convergent and divergent validity of the ROF scale during ramped cycling to exhaustion and 30 min of resting recovery. The final experiment tested the convergent validity of the ROF scale with time of day and physical activity (accelerometer counts) across a whole week.

          Results

          Modal selections of descriptions and diagrams at different levels of exertion and recovery were found during Experiment 1 upon which the ROF scale was constructed and finalised. In Experiment 2, a high level of face validity was indicated, in that ROF was reported to represent fatigue rather than exertion. Descriptor and diagrammatic elements of ROF reportedly added to the coherence and ease of use of the scale. In Experiment 3, high convergence between ROF and various physiological measures were found during exercise and recovery (heart rate, blood lactate concentration, oxygen uptake, carbon dioxide production, respiratory exchange ratio and ventilation rate were all P < 0.001). During ramped cycling to exhaustion ROF and RPE did correspond ( P < 0.0001) but not during recovery, demonstrating discriminant validity. Experiment 4 found ROF to correspond with waking time during each day (Mon–Sun all P < 0.0001) and with physical activity (accelerometer count) (Mon–Sun all P < 0.001).

          Conclusions

          The ROF scale has good face validity and high levels of convergent validity during ramped cycling to exhaustion, resting recovery and daily living activities. The ROF scale has both theoretical and applied potential in understanding changes in fatigue in a variety of contexts.

          Electronic supplementary material

          The online version of this article (doi:10.1007/s40279-017-0711-5) contains supplementary material, which is available to authorized users.

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          Most cited references60

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          Physical activity in the United States measured by accelerometer.

          Richard Troiano, David Berrigan, Kevin Dodd … (2008)
          To describe physical activity levels of children (6-11 yr), adolescents (12-19 yr), and adults (20+ yr), using objective data obtained with accelerometers from a representative sample of the U.S. population. These results were obtained from the 2003-2004 National Health and Nutritional Examination Survey (NHANES), a cross-sectional study of a complex, multistage probability sample of the civilian, noninstitutionalized U.S. population in the United States. Data are described from 6329 participants who provided at least 1 d of accelerometer data and from 4867 participants who provided four or more days of accelerometer data. Males are more physically active than females. Physical activity declines dramatically across age groups between childhood and adolescence and continues to decline with age. For example, 42% of children ages 6-11 yr obtain the recommended 60 min x d(-1) of physical activity, whereas only 8% of adolescents achieve this goal. Among adults, adherence to the recommendation to obtain 30 min x d(-1) of physical activity is less than 5%. Objective and subjective measures of physical activity give qualitatively similar results regarding gender and age patterns of activity. However, adherence to physical activity recommendations according to accelerometer-measured activity is substantially lower than according to self-report. Great care must be taken when interpreting self-reported physical activity in clinical practice, public health program design and evaluation, and epidemiological research.
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            Monitoring Training Load to Understand Fatigue in Athletes

            Shona L. Halson (2014)
            Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
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              The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue.

              E.M.A. Smets, B. Garssen, B. Bonke … (1995)
              The Multidimensional Fatigue Inventory (MFI) is a 20-item self-report instrument designed to measure fatigue. It covers the following dimensions: General Fatigue, Physical Fatigue, Mental Fatigue, Reduced Motivation and Reduced Activity. This new instrument was tested for its psychometric properties in cancer patients receiving radiotherapy, patients with the chronic fatigue syndrome, psychology students, medical students, army recruits and junior physicians. We determined the dimensional structure using confirmatory factor analyses (LISREL's unweighted least squares method). The hypothesized five-factor model appeared to fit the data in all samples tested (AGFIs > 0.93). The instrument was found to have good internal consistency, with an average Cronbach's alpha coefficient of 0.84. Construct validity was established after comparisons between and within groups, assuming differences in fatigue based on differences in circumstances and/or activity level. Convergent validity was investigated by correlating the MFI-scales with a Visual Analogue Scale measuring fatigue (0.22 < r < 0.78). Results, by and large, support the validity of the MFI.
              Article 0 comments Cited 415 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                D. Micklewright:
                ORCID: http://orcid.org/0000-0002-7519-3252
                +44(0)1206 872869 , dpmick@essex.ac.uk
                Journal
                Journal ID (nlm-ta): Sports Med
                Journal ID (iso-abbrev): Sports Med
                Title: Sports Medicine (Auckland, N.z.)
                Publisher: Springer International Publishing (Cham )
                ISSN (Print): 0112-1642
                ISSN (Electronic): 1179-2035
                Publication date (Electronic): 10 March 2017
                Publication date PMC-release: 10 March 2017
                Publication date (Print): 2017
                Volume: 47
                Issue: 11
                Pages: 2375-2393
                Affiliations
                [1 ]ISNI 0000 0001 0942 6946, GRID grid.8356.8, School of Sport, Rehabilitation and Exercise Sciences, , University of Essex, ; Wivenhoe Park, Colchester, Essex, CO4 3SQ UK
                [2 ]ISNI 0000 0004 0408 3579, GRID grid.49481.30, Faculty of Health, Sport and Performance, , University of Waikato, ; Hamilton, New Zealand
                [3 ]ISNI 0000 0004 0607 035X, GRID grid.411975.f, University of Dammam, ; Dammam, Kingdom of Saudi Arabia
                Author information
                http://orcid.org/0000-0002-7519-3252
                Article
                Publisher ID: 711
                DOI: 10.1007/s40279-017-0711-5
                PMC ID: 5633636
                PubMed ID: 28283993
                SO-VID: 0cdd273a-8998-49cd-9b84-79b0cc34f7ba
                Copyright © © The Author(s) 2017
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000269, Economic and Social Research Council;
                Award ID: RES06427001
                Award Recipient :
                Categories
                Subject: Original Research Article
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                issue-copyright-statement © Springer International Publishing AG 2017

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