Tailored activity pacing could help manage fatigue and improve physical activity. However, little is known about how to tailor activity pacing for people with multiple sclerosis. This study aims to evaluate the effect of a tailored activity pacing intervention on fatigue and physical activity behaviours in adults with multiple sclerosis. Twenty-one adults with multiple sclerosis, stratified by age and gender, are randomly allocated to either a tailored pacing or control group. Participants wear an accelerometer for seven days that measures physical activity behaviours, and self-report fatigue at the baseline and four-week follow-up. Physical activity behaviours are assessed by examining activity level (seven-day average activity counts per minute) and activity variability (seven-day average highest activity counts each day divided by activity counts on that day). The intervention improves activity levels (Mean difference = 40.91; 95% Confidence Interval [CI] (3.84–77.96); p = 0.03) and lessens activity variability (Mean difference = −0.63; 95% CI (−1.25–0.02); p = 0.04). No significant effect is found for fatigue (Mean difference = −0.36; 95% CI (−1.02–0.30); p = 0.27). This investigation shows that tailoring activity pacing based on physical activity behaviours and fatigue is effective in improving physical activity levels, without exacerbating fatigue symptoms.

Concepts of how athletes should expend their aerobic and anaerobic energetic reserves are generally based on results of tests where an “all out” strategy is imposed on/required from the athlete. We sought to determine how athletes spontaneously expend their energetic reserves when the only instruction was to finish the event in minimal time, as in competition. Well trained, and task habituated, road cyclists (N = 14) completed randomly ordered laboratory time trials of 500 m, 1000 m, 1500 m and 3000 m on a windload braked cycle ergometer. The pattern of aerobic and anaerobic energy use was calculated from total work accomplished and V·O₂ during the trials. The events were completed in 40.3 ± 0.6 s, 87.4 ± 4.1 s, 133.8 ± 6.6 s and 296.0 ± 7.2 s. The peak V·O₂ during the terminal 200 m of all events was similar (2.72 ± 0.22, 3.01 ± 0.34, 3.23 ± 0.44 and 3.12 ± 0.13 l × min^-1). In all events, the initial power output and anaerobic energy use was high, and decreased to a more or less constant value over the remainder of the event. However, the subjects seemed to reserve some ability to expend energy anaerobically for a terminal acceleration which is contrary to predictions of an “all out” starting strategy. Although the total work accomplished increased with distance (23.14 ± 4.24, 34.14 ± 6.37, 43.54 ± 6.12 and 78.22 ± 8.28 kJ), the energy attributable to anaerobic sources was not significantly different between the rides (17.29 ± 3.82 , 18.68 ± 8.51, 20.60 ± 6.99 and 23.28 ± 9.04 kJ). The results are consistent with the concept that athletes monitor their energetic resources and regulate their energetic output over time in a manner designed to optimize performance.

FOSTER, C., J. J. DE KONING, F. HETTINGA, J. LAMPEN, K. L. LA CLAIR, C. DODGE, M. BOBBERT, and J. P. PORCARI. Pattern of Energy Expenditure during Simulated Competition. Med. Sci. Sports Exerc., Vol. 35, No. 5, pp. 826–831, 2003. To determine how athletes spontaneously use their energetic reserves when the only instruction was to finish in minimal time, and whether experience from repeated performance changes the strategy of recreational athletes. Recreational road cyclists/speed skaters (N = 9) completed three laboratory time trials of 1500 m on a windload braked cycle. The pattern of energy use was calculated from total work and from the work attributable to aerobic metabolism, which allowed computation of anaerobic energy use. Regional level speed skaters (N = 8) also performed a single 1500-m time trial with the same protocol and measurements. The serial trials were completed in (mean ± SD) 133.8 ± 6.6, 133.9 ± 5.8, 133.8 ± 5.5 s (P > 0.05 among trials); and in 125.7 ± 10.9 s in the skaters (P < 0.05 vs cyclists). The [latin capital V with dot above]O2peak during the terminal 200 m was similar within trials (3.23 ± 0.44, 3.34 ± 0.44, 3.30 ± 0.51 (P > 0.05)) versus 3.91 ± 0.68 L·min-1 in the skaters (P < 0.05 vs cyclists). In all events, the initial power output and anaerobic energy use was high and decayed to a more or less constant value (˜25% of peak) over the remainder of the event. Contrary to predictions based on an assumed “all out” starting strategy, the subjects reserved some of their ability to perform anaerobic work for a terminal acceleration. The total work accomplished was not different between trials (43.53, 43.78, and 47.48 kJ in the recreational athletes, or between the cyclists and skaters (47.79 kJ). The work attributable to anaerobic sources was not different between the rides (20.67, 20.53, and 21.12 kJ in the recreational athletes). In the skaters, the work attributable to anaerobic sources was significantly larger versus the cyclists (24.67 kJ). Energy expenditure during high-intensity cycling seems: 1) to be expended in a manner that allows the athlete to preserve an anaerobic energetic contribution throughout an event, 2) does not appear to have a large learning effect in already well trained cyclists, and 3) anaerobic energy expenditure may be the performance discriminating factor among groups of athletes.

The aim of this review was to determine the magnitude of the placebo and nocebo effect on sport performance. Articles published before March 2019 were located using Medline, Web of Science, PubMed, EBSCO, Science Direct, and Scopus. Studies that examined placebo and nocebo effects of an objective dependent variable on sports performance, which included a control or baseline condition, were included in the analysis. Studies were classified into two categories of ergogenic aids: (1) nutritional and (2) mechanical. Cohen's d effect sizes were calculated from 32 studies involving 1513 participants. Small to moderate placebo effects were found for both placebo (d = 0.36) and nocebo (d = 0.37) effects and when separated by nutritional (d = 0.35) and mechanical (d = 0.47) ergogenic aids. The pooled effect size revealed a small to moderate effect size across all studies (d = 0.38). Results suggest that placebo and nocebo effects can exert a small to moderate effect on sports performance.