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Purpose: The influence of interdependency between competitors on pacing decision-making and information-seeking behavior has been explored. This has been done by only altering instructions, and thereby action possibilities, while controlling environment (i.e., competitor behavior) and exercise task., Methods: Twelve participants performed a 4-km time trial on a Velotron cycle ergometer in a randomized, counterbalanced order alone with no virtual opponent (NO), against a virtual opponent with no restrictions (low athlete-opponent interdependency [OP-IND]), or against a virtual opponent who the participant was permitted to overtake only once during the trial (high athlete-opponent interdependency [OP-DEP]). Information-seeking behavior was evaluated using an SMI eye tracker. Differences in pacing, performance, and information-seeking behavior were examined using repeated-measures ANOVA (P < 0.05)., Results: Neither mean power output (NO, 298 ± 35 W; OP-IND, 297 ± 38 W; OP-DEP, 296 ± 37 W) nor finishing time (NO, 377.7 ± 17.4 s; OP-IND, 379.3 ± 19.5 s; OP-DEP, 378.5 ± 17.7 s) differed between experimental conditions. However, power output was lower in the first kilometer of OP-DEP compared with the other experimental conditions (NO, 332 ± 59 W; OP-IND, 325 ± 62 W; OP-DEP, 316 ± 58 W; both P < 0.05), and participants decided to wait longer before they overtook their opponent (OP-IND, 137 ± 130 s; OP-DEP, 255 ± 107 s; P = 0.040). Moreover, total fixation time spent on the avatar of the virtual opponent increased when participants were only allowed to overtake once (OP-IND, 23.3 ± 16.6 s; OP-DEP, 55.8 ± 32.7 s; P = 0.002)., Conclusion: A higher interdependency between athlete and opponent altered pacing behavior in terms of in-race adaptations based on opponent's behavior, and it induced an increased attentional focus on the virtual opponent. Thus, in the context of exercise regulation, attentional cues are likely to be used in an adaptive way according to their availability and situational relevance, consistent with a decision-making framework based on the interdependence of perception and action.

Purpose: To use eye-tracking technology to directly compare information acquisition behavior of experienced and novice cyclists during a self-paced, 10-mile (16.1 km) time trial (TT)., Method: Two groups of novice (n = 10) and experienced cyclists (n = 10) performed a 10-mile self-paced TT on two separate occasions during which a number of feedback variables (speed, distance, power output, cadence, HR, and time) were projected within their view. A large RPE scale was also presented next to the projected information and participants. Participants were fitted with a head-mounted eye tracker and HR monitor., Results: Experienced cyclists performed both TT quicker than novices (F1,18 = 6.8, P = 0.018) during which they primarily looked at speed (9 of 10 participants), whereas novices primarily looked at distance (6 of 10 participants). Experienced cyclists looked at primary information for longer than novices across the whole TT (24.5% ± 4.2% vs 34.2% ± 6.1%; t18 = 4.2; P < 0.001) and less frequently than novices during the last quarter of the TT (49 ± 19 vs 80 ± 32; t18 = -2.6; P = 0.009). The most common combination of primary and secondary information looked at by experienced cyclists was speed and distance, respectively. Looking at 10 different primary-secondary feedback permutations, the novices were less consistent than the experienced cyclists in their information acquisition behavior., Conclusions: This study challenges the importance placed on knowledge of the endpoint to pacing in previous models, especially for experienced cyclists for whom distance feedback was looked at secondary to, but in conjunction with, information about speed. Novice cyclists have a greater dependence on distance feedback, which they look at for shorter and more frequent periods than the experienced cyclists. Experienced cyclists are more selective and consistent in attention to feedback during TT cycling.

Purpose: The objective of this study is to examine risk taking and risk perception associations with perceived exertion, pacing, and performance in athletes., Methods: Two experiments were conducted in which risk perception was assessed using the domain-specific risk taking (DOSPERT) scale in 20 novice cyclists (experiment 1) and 32 experienced ultramarathon runners (experiment 2). In experiment 1, participants predicted their pace and then performed a 5-km maximum effort cycling time trial on a calibrated Kingcycle mounted bicycle. Split times and perceived exertion were recorded every kilometer. In experiment 2, each participant predicted their split times before running a 100-km ultramarathon. Split times and perceived exertion were recorded at seven checkpoints. In both experiments, higher and lower risk perception groups were created using median split of DOSPERT scores., Results: In experiment 1, pace during the first kilometer was faster among lower risk perceivers compared with higher risk perceivers (t(18) = 2.0, P = 0.03) and faster among higher risk takers compared with lower risk takers (t(18) = 2.2, P = 0.02). Actual pace was slower than predicted pace during the first kilometer in both the higher risk perceivers (t(9) = -4.2, P = 0.001) and lower risk perceivers (t(9) = -1.8, P = 0.049). In experiment 2, pace during the first 36 km was faster among lower risk perceivers compared with higher risk perceivers (t(16) = 2.0, P = 0.03). Irrespective of risk perception group, actual pace was slower than predicted pace during the first 18 km (t(16) = 8.9, P < 0.001) and from 18 to 36 km (t(16) = 4.0, P < 0.001). In both experiments, there was no difference in performance between higher and lower risk perception groups., Conclusions: Initial pace is associated with an individual's perception of risk, with low perceptions of risk being associated with a faster starting pace. Large differences between predicted and actual pace suggest that the performance template lacks accuracy, perhaps indicating greater reliance on momentary pacing decisions rather than preplanned strategy.

Purpose: This study aimed to examine the effect of variations in optic flow on perceived and actual running pace and RPE., Methods: Twelve male moderately trained competitive runners performed a self-paced 5-km running reference time trial followed by a three 5-km running self-paced trials under different optic flow conditions (RNORM = actual running speed, RSLOW = actual speed - 25%, and RFAST = actual speed + 25%). Participants were asked to self-report RPE when they thought they had reached each kilometer., Results: There was no difference in the 5-km completion times (P > 0.05) or actual pace (P > 0.05) between the optic flow conditions. A greater distance was covered between the perceived kilometer points during RSLOW compared with RNORM (P < 0.01) and RFAST (P < 0.01). RPE (normalized for running distance) was lower during RSLOW compared with RNORM (P < 0.01) and RFAST (P < 0.01)., Conclusions: Different rates of optic flow lead to an apparent compression or elongation of perceived distance during running, with slow optic flow resulting in an increased ratio of perceived to actual running distance. Pacing was not different in the slow optic flow condition, despite lower perceived exertion, which is contrary to the predictions of the RPE template model, hazard scores, and estimated time limits.

Athletes anticipatorily set and continuously adjust pacing strategies before and during events to produce optimal performance. Self-regulation ensures maximal effort is exerted in correspondence with the end point of exercise, while preventing physiological changes that are detrimental and disruptive to homeostatic control. The integration of feedforward and feedback information, together with the proposed brain's performance modifiers is said to be fundamental to this anticipatory and continuous regulation of exercise. The manipulation of central, regulatory internal and external stimuli has been a key focus within deception research, attempting to influence the self-regulation of exercise and induce improvements in performance. Methods of manipulating performance modifiers such as unknown task end point, deceived duration or intensity feedback, self-belief, or previous experience create a challenge within research, as although they contextualize theoretical propositions, there are few ecological and practical approaches which integrate theory with practice. In addition, the different methods and measures demonstrated in manipulation studies have produced inconsistent results. This review examines and critically evaluates the current methods of how specific centrally controlled performance modifiers have been manipulated, within previous deception studies. From the 31 studies reviewed, 10 reported positive effects on performance, encouraging future investigations to explore the mechanisms responsible for influencing pacing and consequently how deceptive approaches can further facilitate performance. The review acts to discuss the use of expectation manipulation not only to examine which methods of deception are successful in facilitating performance but also to understand further the key components used in the regulation of exercise and performance.

Purpose: To compare pacing and performance of schoolchildren between running tasks where the end point was defined in units of either distance or time., Methods: Thirty-eight schoolchildren (age = 12.6 ± 0.5 yr, mass = 46.2 ± 7.5 kg, stature = 150 ± 7 cm) first performed a best-effort 750-m running task on a 150-m running track. The schoolchildren were split into two groups, matched for sex, age, and running performance, before completing the second running trial. One group repeated the 750-m running task (distance-distance group), whereas the other completed a running task to a time that had been matched to their previous 750-m performance (distance-time group). Pace was measured every 10% segment throughout each run., Results: No difference between trials in average running speed was found among the distance-distance group (13.64 ± 1.59 vs. 13.68 ± 1.62 km·h(-1), P > 0.05); however, the distance-time group were slower during the time task compared with during the distance task (13.84 ± 1.61 vs. 13.37 ± 1.57 km·h(-1), P < 0.005). There was no difference in pacing pattern between trials among the distance-distance group (P > 0.05), but the distance-time group exhibited a slower overall slower pace with no end spurt (P < 0.0001). During the time task, children looked at their watches more frequently the nearer they got to the end point (ρ = 0.933, P < 0.0001)., Conclusions: Schoolchildren find it easier to use spatial cues during a pacing task compared with temporal cues. Running pace in all trials followed a classic U-shaped pattern; however, lap-by-lap oscillations in pacing substrategies were also evident, which may be a psychological coping strategy.

Purpose: Schoolchildren who cycle to school have higher cardiorespiratory fitness (CRF) than those who are driven or use public transport. The purpose of this study was to determine whether recreational cycling is similarly associated with CRF., Methods: Participants were 5578 (54% males) English schoolchildren (10.0-15.9 yr). All reported frequency of recreational cycling events via 7-d recall. Responses were categorized as follows: "noncyclists" = 0, "occasional cyclists" = 1-4, or "regular cyclists" = 5+ (times per week). CRF was assessed using the 20-m shuttle run test with performance classified as "fit" or "unfit" based on FITNESSGRAM standards., Results: Overall, 26% of males and 46% of females were noncyclists. Compared with noncyclists, the 40% of males and 42% of females classified as occasional cyclists were more likely to be fit (males: odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.07-1.59; females: OR = 1.41, 95% CI = 1.13-1.76). Regular cyclists (34% males and 12% females) had a greater likelihood still of being classified as fit (males: OR = 1.58, 95% CI = 1.29-1.95; females: OR = 1.55, 95% CI = 1.09-2.20). No odds remained significant after adjusting for physical activity. Removal of participants who cycled to school had little overall effect on the likelihood of being classified as being fit., Conclusions: Previous research has focused only on young people's commuter cycling habits, at the expense of the more common activity of recreational cycling. Recreational cycling may provide an alternative target for interventions to increase physical activity and improve CRF youth. Recreational cycling could potentially serve as a way to gain cycling confidence and establish habits that act as precursors to commuter cycling.

Purpose: The study's purpose was to examine differences in pacing strategy between schoolchildren of different age, gender, and stage of cognitive development., Methods: Schoolchildren (n = 106) from four age groups (5-6, 8-9, 11-12, and 14 yr) participated in this study. Each schoolchild completed four conservation tasks to evaluate his or her Piagetian stage of cognitive development. Each schoolchild then performed a best-effort running task on a 150-m running track that was video recorded to analyze pace at 5% increments. The length of the run was varied for each age group to ensure that all schoolchildren were running for approximately 4 min (5-6 yr = 450 m, 8-9 yr = 600 m, 11-12 yr = 750 m, and 14 yr = 900 m)., Results: Differences in pacing strategy were found between schoolchildren of different age (P < 0.0001), gender (P < 0.0001), and cognitive development (P < 0.0001). Pacing differences were also found between age groups after controlling for cognitive development (P < 0.001), between cognitive abilities after controlling for age (P < 0.01), and between genders after controlling for both age (P < 0.0001) and cognitive ability (P < 0.0001)., Conclusions: Younger schoolchildren with less advanced cognitive development exhibited a negative pacing strategy indicating an inability to anticipate exercise demand. Older schoolchildren at a more advanced stage of cognitive development exhibited a more conservative U-shaped pacing strategy characterized by faster running speeds during the first 15% and last 20% of the run. Anticipatory pacing strategy seems to be related to both the age and cognitive development of schoolchildren.