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.

Objective To investigate how experience and feedback influence pacing and performance during time trial cycling. Design Twenty-nine cyclists performed three 20 km cycling time trials using a Computrainer. The first two time trials (TT1 and TT2) were performed (1) without any performance feedback (n = 10), (2) with accurate performance feedback (n = 10) or (3) with false feedback showing the speed to be 5% greater than the actual speed (n = 9). All participants received full feedback during the third time trial (TT3), and their performance and pacing data were compared against TT2. Results Completion time, average power and average speed did not change among the false feedback group, but their pacing strategy did change as indicated by a lower average cadence, 89.2 (SD 5.2) vs 96.4 (6.8) rpm, p<0.05, and higher power during the first 5 km (SMD = 39, 36, 36, 27 and 27 W for 1–5 km respectively). Pacing changed among the blind feedback group indicated by a faster completion time, 35.9 (3.1) vs 36.8 (4.4) min, p<0.05, and power increases during the final 5 km (SMD = 14, 13, 18, 23 and 53 W for 16–20 km respectively). No performance or pacing changes were observed among the accurate feedback group. Conclusions Pacing is influenced by an interaction between feedback and previous experience. Conscious cognitive processes that lead to ratings of perceived exertion and pacing appear to be influenced by previous experience.

The aim of an optimal pacing strategy during exercise is to enhance performance whilst ensuring physiological limits are not surpassed, which has been shown to result in a metabolic reserve at the end of the exercise. There has been debate surrounding the theoretical models that have been proposed to explain how pace is regulated, with more recent research investigating a central control of exercise regulation. Deception has recently emerged as a common, practical approach to manipulate key variables during exercise. There are a number of ways in which deception interventions have been designed, each intending to gain particular insights into pacing behaviour and performance. Deception methodologies can be conceptualised according to a number of dimensions such as deception timing (prior to or during exercise), presentation frequency (blind, discontinuous or continuous) and type of deception (performance, biofeedback or environmental feedback). However, research evidence on the effects of deception has been perplexing and the use of complex designs and varied methodologies makes it difficult to draw any definitive conclusions about how pacing strategy and performance are affected by deception. This review examines existing research in the area of deception and pacing strategies, and provides a critical appraisal of the different methodological approaches used to date. It is hoped that this analysis will inform the direction and methodology of future investigations in this area by addressing the mechanisms through which deception impacts upon performance and by elucidating the potential application of deception techniques in training and competitive settings.