Attentional focus during endurance activity is a dynamic process. To optimize performance, athletes must monitor both internal (e.g., bodily states) and external (e.g., environmental) stimuli and engage appropriate cognitive strategies to cope with task demands (6). Much research underpins this contention, demonstrating that a focus on task-relevant self-regulatory thoughts (e.g., relaxing and cadence/rhythm) may improve movement economy (7) or optimize pace (8). Conversely, an excessive focus directed toward bodily sensations (e.g., breathing and movement) may reduce movement efficiency (32) and diminish performance.
Alongside an appreciation of the isolated effects of attentional foci, an understanding of the situational determinants of strategy selection is also important (6). Adapting successfully to varying contexts requires cognitive control or the intentional selection of thoughts and actions based on task demands (12,27). Situational factors may also necessitate differing forms of cognitive control, specifically proactive, goal-driven control (e.g., planning a pacing strategy) or reactive, stimulus-driven processes (e.g., responding to environmental changes) (4,6,10,27). Recently, Brick et al. (6) proposed a metacognitive framework to allow a better understanding of these attentional operations during endurance activity. Metacognition can be defined as an individual’s insight into and control over their own mental processes (15). The metacognitive framework (6) highlights the importance of metacognitive skills (e.g., planning, monitoring, or reviewing one’s thoughts) and metacognitive experiences (e.g., feelings of task difficulty, or judgments about effective/ineffective attentional foci) to cognitive strategy selection and implementation. Highly developed metacognitive abilities may be a feature of experience and familiarity with task demands, however (23). Accordingly, the ability of individuals to engage a focus of attention appropriate to situational constraints deserves further exploration.
During self-paced endurance activity, including individual time trials, perceptions of exertion are considered central to pace regulation (31,37). How perceptions of exertion are generated is a topic of debate, however. Within some models, central regulation of pacing strategy is the result of feedforward control in response to nonconscious processing of afferent feedback from physiological systems (29,31,37). However, this contention has been challenged by the evidence that perceived exertion may be independent of afferent feedback (24). An alternative approach, the psychobiological model, considers the role of corollary discharge or the conscious awareness of efferent signals believed to originate from premotor and motor areas of the cortex (11,30,33). Within this model, the conscious regulation of pace is determined by cognitive and motivational factors, including perception of effort, potential motivation, knowledge of distance/time remaining, and previous experience of perception of effort during exercise of varying intensity and duration (30,33).
Given the importance of effort perceptions to endurance performance, evidence suggesting that attentional focus may alter this relationship deserves further consideration (5,26). In addition to understanding why attentional strategies are effective, recognizing situational factors that dictate when particular foci are more useful is also important. One such context relates to perception of control over pacing. In a recent review, Brick et al. (5) intimated that control over pacing may impact on attentional focus and subsequent performance outcomes. Specifically, in self-controlled (SC) pace designs, performance tended to improve—without an elevation in effort perception—when subjects engaged active self-regulatory strategies (8,22). In contrast, during externally controlled (EC) pace tasks, an excessive focus on bodily sensations tended to increase effort perceptions, whereas distractive strategies had the opposite effect (34).
Accordingly, the purpose of the current study was to present experienced endurance runners with contexts where task constraints were modified. The primary aim was to investigate the effect of manipulating perceptions of pace control on attentional focus, physiological, and psychological measures during running. It was hypothesized that athletes would adapt attentional focus to cope effectively with task demands. The use of effort perceptions to regulate self-paced endurance activity and the concomitant impact on attentional foci were also of interest. Therefore, a secondary aim was to determine the reproducibility of self-paced running performance when regulated by perceptions of effort.
METHODS
Subjects, ethics, and informed consent.
Subjects were recruited via email to local running clubs. Twenty experienced endurance runners (Table 1) volunteered to take part and were given no incentives for participation. All subjects were healthy, free from injury, engaged in regular running training, and were accustomed to treadmill running. The study was approved by the institutional research ethics committee, and all participants completed a medical history questionnaire and gave written informed consent before taking part in the study. The study requirements were outlined to subjects but they were not informed of the aims and hypotheses. Subjects were also naive to specific time trial protocols and were requested not to discuss the study with other subjects.
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TABLE 1: Demographic and training characteristics of subjects (n = 20).
Study design and procedures.
A repeated-measures crossover design was used. Subjects visited the laboratory on five occasions, each separated by 3–8 d to limit fatigue and training adaptations. Trials were performed at the same time of day (±3 h). Subjects maintained normal training and sleep patterns throughout the duration of the study and refrained from strenuous activity in the 24 h preceding each trial. Before the first session, subjects recorded a 24-h food diary and were asked to maintain similar dietary intake before subsequent visits. Subjects were asked to avoid caffeine and food, and drink 500 mL of water in the 2 h before each session. Body mass was recorded before each trial to indicate no significant variations in hydration status.
Maximal oxygen consumption (V˙O2max).
On the initial visit, subjects completed an incremental exercise test to volitional exhaustion on a treadmill (h/p/cosmos quasar; h/p/cosmos Sports & Medical GmbH, Traunstein, Germany) with continuous measurement of respiratory gas exchange using an online metabolic cart calibrated before each test (Quark C-PET; Cosmed Srl, Rome, Italy). After a 5-min warm-up at a self-selected pace, subjects began at a light intensity based on their ability, with the intention of reaching volitional exhaustion within 10–15 min. Stages lasted 2 min, with 2 km·h−1 increments for each of the first three stages followed by 1 km·h−1 increments to volitional exhaustion. The treadmill gradient was maintained at 1%. Volitional exhaustion was reached in 13.9 ± 1.4 min. HR was measured continuously by wireless telemetry (Cosmed HR monitor). V˙O2max was determined as the highest value for a 10-breath rolling average. In all the tests, two or more criteria for V˙O2max were met (19).
Experimental measures.
During visits 2–5, subjects completed a 3-km time trial on the laboratory treadmill. On arrival at the laboratory, subjects were informed of the protocol for the ensuing time trial (see time trials). After a check for understanding, subjects completed the Brunel Mood Scale (BRUMS) (36) on which they were instructed to “circle the answer which best describes how you feel right now.” To determine potential motivation, subjects completed an adapted state motivation questionnaire (25) and two 11-point Likert-type scales to determine willingness to invest maximal physical and mental effort (0 = not willing, 10 = willing) (38,39). Before the warm-up, subjects’ body mass (Seca 862, Hamburg, Germany) and resting blood lactate concentration were recorded (Lactate Pro 2; Arkray Inc., Kyoto, Japan).
During each time trial recording of running speed, HR (Polar RS400, Kempele, Finland), RPE (Borg RPE 6–20 scale) (3), and affective valence (Feeling Scale) (17) were taken at 200 m and at each 400-m distance interval thereafter. RPE and affective valence scales were projected on a screen 3.5 m in front of the treadmill and removed once the subjects had indicated their RPE and affect over the preceding 200 m. Before the perceived exertion clamped (PE) time trial, subjects were informed that their reported RPE could vary from the instructed RPE if they perceived their actual exertion to be different.
Time trials.
Before each time trial, subjects warmed up for 5 min at a pace equivalent to 70% of the maximum HR recorded during the incremental test, followed by 2-min rest (38). To provide knowledge of the distance elapsed/remaining (30,33), only the treadmill distance display was visible to the subjects. However, the user terminal was interfaced with a computer (h/p/cosmos pc software) so that all time trial data were visible to the experimenters. A video camera was used to record data for later analysis. Subjects received no other feedback or verbal encouragement throughout each time trial. A fan was positioned at the front right of the treadmill during each trial to ensure consistency of laboratory conditions.
Time trials 1 and 2 were SC trials. Before each trial, subjects were instructed how to manipulate treadmill speed on the user terminal and were informed they could pace the trial freely, but to complete it as quickly as possible. The first time trial served as a familiarization trial. The second trial replicated the familiarization trial. Paired-sample t-tests indicated no differences between trials in running speed, completion time, HR, posttrial blood lactate, perceived exertion, or affective valence, or on frequency ratings for any attentional focus category (see Post–time trial measures and attentional focus interview section). The fastest trial was used as each subject’s SC trial for subsequent analysis.
Time trials 3 and 4 were completed in a randomized, counterbalanced order (www.random.org). Time trial 3 was a rating of PE trial. During PE, subjects were instructed to maintain varying perceptions of exertion, replicating those self-reported during SC. Subjects were issued with an RPE instruction at each distance interval (e.g., 200 m, 600 m, etc.) to attain by the next 200-m segment (e.g., 400–600 m, 800–1000 m, etc.). Subjects were informed beforehand and reminded during the trial that RPE was in the context of a 3-km time trial they were attempting to complete as quickly as possible (30,33). Subjects could manipulate the treadmill speed throughout. Time trial 4 was an EC pace trial during which the experimenter controlled the treadmill speed using the manufacturer’s software controls. Before EC, subjects were informed the trial would be completed as quickly as possible but the experimenter would control the speed. Pacing replicated the self-selected strategy adopted during SC. Subjects were blind to the origin of the RPE instructions and the pacing strategy implemented during PE and EC, respectively.
Post–time trial measures and attentional focus interview.
After each time trial, participants completed the BRUMS, on which they were instructed to “circle the answer which best describes how you felt during the 3-km time trial,” and the state motivation questionnaire as retrospective measures. As a manipulation check, subjects rated their perception of control over pacing on an 11-point Likert-type scale (0 = no control, 10 = complete control). During a posttrial interview, subjects rated how frequently they focused on thoughts from attentional focus categories (5,6) during the time trial on 11-point Likert-type frequency scales (one item per category) with verbal descriptors (0 = never, 10 = always) (40). Subjects also recounted specific foci engaged and were able to view attentional focus category information to assist recall (see Document, Supplemental Digital Content 1, attentional focus rating scales and checklist, https://links.lww.com/MSS/A607). All interviews were digitally recorded to check for accuracy.
Statistical analysis.
The effect of the conditions (SC, PE, EC) on the pretrial states (i.e., body mass, resting blood lactate, willingness to invest physical and mental effort, success and interest motivation), time trial performance (i.e., completion time, running speed), physiological (i.e., HR and posttrial blood lactate), and psychological measures (i.e., RPE, affect, and mood states); the manipulation check; and the attentional focus frequency ratings were analyzed using repeated-measures multivariate ANOVA (MANOVA). If assumptions of sphericity were violated, the Greenhouse–Geisser correction was used to report the analyses. Post hoc pairwise comparisons with Sidak-adjusted P values were conducted where a significant F-ratio was observed. Statistical significance was accepted as P < 0.05 (two tailed). Reporting of analyses focused on comparisons between SC and EC, and between SC and PE. Cohen’s d (9) values are provided as an estimate of effect size where relevant. Where appropriate, 95% confidence intervals (CI) are reported for post hoc pairwise comparisons. All data analyses were conducted using the Statistical Package for the Social Sciences (IBM Statistics 22.0; SPSS Inc., Chicago, IL).
RESULTS
Reporting of within time trial distance interval measures (i.e., speed, HR, affect, and RPE) will focus on mean time trial values. A more detailed analysis is available on the online digital content (see Figure, Supplemental Digital Content 2, distance interval analyses, https://links.lww.com/MSS/A608).
Pretrial state measures.
The mean duration between SC and EC was 7.9 ± 4.2 d, and that between SC and PE was 9.3 ± 4.6 d. Consistency of pretrial states (Table 2) indicated no differences for body mass, resting blood lactate, willingness to invest physical effort, willingness to invest mental effort, or success motivation. Interest motivation was higher before EC than that before SC (mean difference (MD) = 0.95; 95% CI, 0.03–1.87; P = 0.042, d = 0.44). Retrospective measures indicated no differences in success or interest motivation between conditions. As a consequence, the effect of condition was further analyzed using a repeated-measures multivariate ANCOVA (MANCOVA) where appropriate, with pre-EC interest motivation controlled as the covariate.
TABLE 2: Measures for pretrial variables, time trial data, and manipulation check for SC, PE, and EC.
Time trial performance.
Mean running speed (Table 2 and Fig. 1A) was slower during PE than that during SC (MD = −1.33 km·h−1; 95% CI, −2.01 to −0.66; P < 0.001, d = 0.94), resulting in a slower completion time for PE (MD = 1.18 min; 95% CI, 0.57–1.78; P < 0.001, d = 0.84). Neither mean speed nor completion time differed between SC and EC. During SC, subjects made 12.1 ± 3.7 pace adjustments, most occurring within the first 600 m (5.1 ± 2.6) and the last 400 m (2.6 ± 1.2).
FIGURE 1: Running speed (A), HR (B), affective valence (C), and RPE (D) during 3-km time trials. Error bars illustrate SEM. Symbols denote main effect of condition: #Mean speed slower for PE than that for SC (P < 0.001). *HR higher for SC than those for both EC (P < 0.001) and PE (P < 0.001). ^Affective valence more positive for PE than that for SC (P = 0.033).
Physiological measurements.
HR (Table 2 and Fig. 1B) was higher during SC compared with both EC (MD = 3.24 bpm; 95% CI, 1.51–4.95; P < 0.001, d = 0.35) and PE (MD = 9.54 bpm; 95% CI, 5.96–13.12; P < 0.001, d = 0.86). A follow-up Pearson’s product moment correlation revealed that the difference in HR between SC and EC was negatively correlated with the number of pace adjustments made during SC (r = −0.513, P = 0.021). Blood lactate (Table 2) was lower after PE compared with SC (MD = −2.80 mmol·L−1; 95% CI, −5.43 to −0.159; P = 0.036, d = 0.67). There was no difference in posttrial blood lactate between SC and EC.
Psychological measures and manipulation check.
There was no main effect of condition for RPE on MANOVA or MANCOVA outcomes (Table 2 and Fig. 1D). Mean affective valence during PE (Table 2 and Fig. 1C) was more positive than that during SC (MD = 0.81; 95% CI, 0.06–1.56; P = 0.033, d = 0.52). There was no main effect of condition for any mood states reported pretrial or retrospectively on MANOVA or MANCOVA outcomes (Table 3). The posttrial manipulation check (Table 2) revealed a reduced perception of control over pacing between EC and SC (MD = −7.50; 95% CI, −9.27 to −5.73; P < 0.001, d = 3.64) but not between SC and PE.
TABLE 3: Mean ± SD for mood states (BRUMS) reported pretrial and retrospectively posttrial.
Post–time trial attentional focus frequency rating and qualitative interviews.
Attentional focus frequency ratings are provided in Fig. 2. Internal body sensations were monitored more frequently during PE than during both SC (MD = 1.55; 95% CI, 0.16–2.94; P = 0.026, d = 0.83) and EC (MD = 1.45; 95% CI, 0.39–2.52; P = 0.006, d = 0.90). There was no main effect of condition for active self-regulation (P = 0.077), outward monitoring (P = 0.262), or distraction (P = 0.223).
FIGURE 2: Attentional focus frequency ratings for each condition. Error bars illustrate SEM. Symbol denotes Sidak-adjusted pairwise difference. *Internal sensory monitoring higher during PE than those during SC (P = 0.026) and EC (P = 0.006).
The primary active self-regulatory thoughts reported during SC were pacing/tactics (95% of subjects), chunking (i.e., mentally breaking the 3-km distance down to smaller segments, 80%), and improving running technique (65%). These were pacing/tactics (70%), relaxing (55%), and improving running technique (40%) during PE, whereas during EC, subjects reported improving running technique (75%), relaxing (60%), and cadence/rhythm (55%). Bodily sensations most frequently monitored were breathing, body movement/form, and overall effort/feel. Breathing was monitored by 80% of subjects during SC, 65% during PE, and 50% during EC. Body movement was monitored by 60% during SC, 65% during PE, and 45% during EC, whereas the overall effort/feel was monitored by 55% during SC, 80% during PE, and 45% during EC. The distance display was the most monitored outward source of information reported by 95% of subjects during SC, 85% during PE, and 80% during EC. Finally, 40% of subjects reported distraction during SC, 35% during PE, and 55% during EC.
Individual differences in RPE responses during SC and EC time trials.
Further analysis of the RPE data suggested individual differences in response to the EC trial (Fig. 3). Specifically, nine individuals perceived exertion during EC to be higher than that during SC, and 11 perceived lower. Consequently, between-group differences were analyzed using MANOVA with increased/decreased RPE during EC as the between-group factor. RPE reported during SC did not differ, but there was a between-group difference in RPE reported during EC (F1,18 = 7.83, P = 0.012, d = 0.80). Mean RPE increased from SC (12.7 ± 1.6) to EC (13.9 ± 1.4) for those who reported EC harder, and decreased from SC (12.5 ± 1.9) to EC (11.7 ± 2.0) for those who found EC easier. Furthermore, subjects who perceived an elevated RPE during EC also reported a greater frequency of internal sensory monitoring than those who reported a lowered RPE (mean ± SD, 7.2 ± 1.8 vs 5.6 ± 1.4, respectively; 95% CI, 0.08, 3.10; P = 0.041, d = 0.99). The groups did not differ on running experience or any other attentional focus, physiological, or psychological variable.
FIGURE 3: Individual subject data (gray lines) for differences in RPE reported during SC and EC time trials. Thicker black lines represent mean RPE ± SEM for subjects perceiving EC easier (full lines), and more difficult (dashed lines) than SC. *Difference between groups in mean RPE reported during EC (P = 0.012).
DISCUSSION
The primary aim of this investigation was to determine the effects of manipulating perceptions of pace control on attentional focus, physiological, and psychological measures during 3-km time trial running. This study was the first to compare these outcomes under SC versus EC pace conditions. An important finding was that EC pace running altered the content of subjects’ self-regulatory cognitions. Specifically, during EC, subjects focused less attention on self-regulatory thoughts related to pacing and more on relaxation and optimizing their running action. HR was also 2% lower during the EC trial than that during the SC trial despite an identical pacing strategy between trials. The second aim was to determine the reproducibility of self-paced running when regulated by perceptions of effort. Mean completion time was 10% slower during the PE time trial, despite identical effort perceptions to the SC trial. Subjects also reported a large increase in internal sensory monitoring during the PE trial.
Altering perceptions of pace control appeared to have a profound impact on runners’ focus of attention. During SC, for example, almost all subjects focused on pacing, monitoring the distance display, and chunking (i.e., mentally breaking the 3-km distance down to smaller segments to assist pacing decisions). In contrast, during EC, the majority of subjects focused on relaxing and improving both running technique and cadence/rhythm. Furthermore, fewer subjects reported monitoring breathing and body movement during EC in comparison with SC. The altered focus of attention also coincided with a small reduction in HR during the EC trial, which cannot be explained by treadmill manipulations or a training effect (18,21,28).
The potentially beneficial impact of focusing on relaxing and optimizing running action may have important implications for endurance running performance. Previous studies, for example, have demonstrated improved running economy and/or reduced HR in endurance athletes experienced at using relaxation strategies (7) or running at a preferred cadence (20). Additionally, concentrating on improved movement technique has been shown to optimize running performance (13). In contrast, monitoring highly automated processes such as breathing or movement execution may increase HR and the oxygen cost of running (32). The findings of the present study also emphasize the significance of metacognitive processes to attentional focus within varying contexts (6). Specifically, the data suggest that during the EC time trial, task-relevant monitoring of situational variables (e.g., bodily sensations) stimulated cognitive control and selection of cognitive strategies more conducive to a lowered oxygen cost of running.
The differences in subjects’ self-regulatory cognitions during the SC and EC time trials may have further significance. Focusing on pace-related thoughts during the SC trial implies a need for proactive, goal-driven cognitive control (4,6,10). In such circumstances, sustained activation of the prefrontal cortex is required to control cognition and guide behavior, resulting in a greater demand on cognitive resources (4,27). Furthermore, study of brain activity indicates that areas including the prefrontal, premotor, and sensorimotor cortices are more active when changes in locomotion speed are prepared in advance (35), as would occur during self-paced running. In contrast, during EC an identical pacing strategy may not have required proactive cognitive control. Instead, reactive or stimulus-driven attentional control (4,6,10) may have been more appropriate, whereby subjects could reactively employ cognitive strategies (e.g., to relax) based on periodic monitoring. Although reactive cognitive control may also have been prevalent during the SC trial, it was likely the dominant form of control during the EC trial. Reactive control is considered less demanding on cognitive resources than proactive control (4). Accordingly, a reduction in central regulation (31) may represent an additional benefit of EC pace running.
Although recognizing limitations of the present study (i.e., treadmill running and subjective reporting of attentional focus), the potential reduction in both cognitive and physiological demands when pace is set may have practical performance benefits. Although Bath et al. (1) reported no performance effect for subjects running with a pacemaker, the second runner in that study adjusted their pace in reaction to the subject’s strategy, thus not truly acting as a pacemaker. However, a study of pack running during World Half Marathon Championships (16) noted that athletes who ran in packs with similar ability opponents (i.e., pacemakers) during the entire race increased pace over the final 1.1 km more than any other group (e.g., solo runners or occasional pack runners). Whether this was a result of increased competition (16,39) or reduced wind resistance (31) demands further study. It may be that additional advantages are accrued when employing less resource demanding reactive cognitive control and cognitive strategies conducive to increased running efficiency.
Although stimulus-driven attentional control may be less demanding on cognitive resources, a more in-depth analysis of the data suggests that an excessive focus on some stimuli may be counterproductive. Although mean RPE did not differ between EC and SC trials, large individual differences in RPE responses were apparent (Fig. 3). Specifically, nine subjects, including all five females, perceived EC to be more difficult than SC. This group also reported monitoring bodily sensations frequently during EC, whereas those who perceived EC to be easier monitored occasionally/often. Increased monitoring of bodily sensations has been reported to intensify perceptions of exertion (34). Thus, the findings partially support the original hypothesis in that some but not all subjects adapted attentional focus to cope with the constraints imposed by the EC trial. This may be due to a lack of task-specific experience, for example (23,30,33), while the influence of gender warrants further research attention.
The second aim was to determine the reproducibility of self-paced running when regulated based on perceptions of effort. In this regard, a major finding was that, on average, PE was completed 10% slower than SC. This was despite no reported difference in perceived exertion or state motivation between SC and PE trials. The slower running speed (by 8.7%) during PE resulted in a reduced HR (by 5.8%) and a lower posttrial blood lactate concentration (by 25.5%). Affective valence was also more positive during EC, which may reflect the slower running speed and decreased blood lactate (14). Collectively, the findings support suggestions that effort perceptions may be independent of afferent feedback from cardiovascular and metabolic stress (24). However, the slower running speed during PE should, theoretically, also reduce efferent output and activity in premotor and motor areas of the cortex, regions believed to be responsible for the corollary discharges generative of effort perception (11). As with individual differences reported between SC and EC trials, however, consideration of attentional focus responses may also resolve this apparent anomaly.
During the PE trial, subjects monitored bodily sensations most of the time as opposed to often/frequently during SC (Fig. 2). In addition, a greater number of athletes reported monitoring overall effort/feel (80%) and body movement (65%) during PE. From an attentional focus perspective (6), the findings suggest that excessive internal sensory monitoring without task-appropriate self-regulatory (8,22), outward (38,39), or distractive (34) foci may amplify feelings of task difficulty. This may result from an increased conscious awareness of corollary discharge and an attendant elevation in effort perceptions. Consequently, during PE, a decreased intensity was required to maintain the instructed RPE. The findings emphasize the importance of a context-appropriate focus of attention during endurance activity (5,6).
CONCLUSIONS AND FUTURE RECOMMENDATIONS
This is the first study to directly compare SC trial and EC trial pace endurance tasks. An important finding was that subjects employed attentional strategies (e.g., relaxing and optimizing running action) conducive to improved running efficiency during the EC trial. Attentional control during EC pace running may also be less demanding on cognitive resources. However, increased internal sensory monitoring coincided with elevated effort perceptions in some runners during the EC trial. Compared with the SC trial, excessive monitoring of bodily sensations (e.g., overall effort/feel and body movement) was also accompanied by a slower running speed and completion time during the PE trial. This study highlights the need for a task-appropriate focus of attention during running and supports suggestions that attentional focus may be an important determinant of endurance performance (2,26).
Based on the present findings, further research is required to explore the performance implications of EC pace running in an ecologically valid setting (e.g., running with pacemakers). Given that all five female subjects reported increased effort perceptions during the EC trial, the potentially moderating influence of gender should also be investigated. Future research is also needed to determine the cortical activity involved during EC versus SC endurance tasks. Finally, from an applied practice perspective, the findings suggest attentional focus interventions may prove beneficial for some athletes to adapt successfully to task demands. Performance advantages may be accrued by those athletes adopting a context-appropriate focus of attention.
The authors would like to acknowledge all subjects for their efforts. They would like to express their gratitude to Ulster University for use of their laboratory facilities and to Dr. Ian Lahart for reviewing an earlier version of this manuscript. They also wish to thank Laura Evans, Sabrina Gallen, Louise Kane, and Eoghan Mullan for their assistance with data collection.
The authors have no conflicts of interest. This study received no sources of funding. The results do not constitute endorsement by the American College of Sports Medicine.
REFERENCES
1. Bath D, Turner LA, Bosch AN, et al. The effect of a second runner on pacing strategy and RPE during a running time trial.
Int J Sports Physiol Perform. 2012; 7(1): 26–32.
2. Bigliassi M. Corollary discharges and fatigue-related symptoms: the role of attentional focus.
Front Psychol. 2015; 6: 1002.
3. Borg GA. Psychophysical bases of perceived exertion.
Med Sci Sports Exerc. 1982; 14(5): 377–81.
4. Braver TS. The variable nature of cognitive control: a dual mechanisms framework.
Trends Cogn Sci. 2012; 16(2): 106–13.
5. Brick N, MacIntyre T, Campbell M. Attentional focus in endurance activity: new paradigms and future directions.
Int Rev Sport Exerc Psychol. 2014; 7(1): 106–34.
6. Brick N, MacIntyre T, Campbell M. Metacognitive processes in the self-regulation of performance in elite endurance runners.
Psychol Sport Exerc. 2015; 19: 1–9.
7. Caird SJ, McKenzie AD, Sleivert GG. Biofeedback and relaxation techniques improves running economy in sub-elite long distance runners.
Med Sci Sports Exerc. 1999; 31(5): 717–22.
8. Clingman JM, Hilliard DV. Race walkers quicken their pace by tuning in, not stepping out.
Sport Psychol. 1990; 4: 23–32.
9. Cohen J.
Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillside (NJ): Laurence Erlbaum Associates; 1988.
10. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain.
Nat Rev Neurosci. 2002; 3(3): 201–15.
11. de Morree HM, Klein C, Marcora SM. Perception of effort reflects central motor command during movement execution.
Psychophysiology. 2012; 49: 1242–53.
12. Dixon ML. Cognitive control, emotional value, and the lateral prefrontal cortex.
Front Psychol. 2015; 6: 758.
13. Donohue B, Barnhart R, Covassin T, Carpin K, Korb E. The development and initial evaluation of two promising mental preparatory methods in a sample of female cross country runners.
J Sport Behav. 2001; 24(1): 19–30.
14. Ekkekakis P. Pleasure and displeasure from the body: perspectives from exercise.
Cogn Emot. 2003; 17(2): 213–39.
15. Flavell JH. Metacognition and cognitive monitoring: a new area of cognitive developmental inquiry.
Am Psychol. 1979; 34: 906–11.
16. Hanley B. Pacing profiles and pack running at the IAAF World Half Marathon Championships.
J Sports Sci. 2015; 33(11): 1189–95.
17. Hardy CJ, Rejeski WJ. Not what, but how one feels: the measurement of affect during exercise.
J Sport Exerc Psychol. 1989; 11: 304–17.
18. Hickson RC, Hagberg JM, Ehsani AA, Holloszy JO. Time course of the adaptive responses of aerobic power and heart rate to training.
Med Sci Sports Exerc. 1981; 13(1): 17–20.
19. Howley ET, Bassett DR Jr, Welch HG. Criteria for maximal oxygen uptake: review and commentary.
Med Sci Sports Exerc. 1995; 27(9): 1292–301.
20. Hunter I, Smith GA. Preferred and optimal stride frequency, stiffness and economy: changes with fatigue during a 1-h high-intensity run.
Eur J Appl Physiol. 2007; 100(6): 653–61.
21. Jones AM, Carter H. The effect of endurance training on parameters of aerobic fitness.
Sports Med. 2000; 29(6): 373–86.
22. LaCaille RA, Masters KS, Heath EM. Effects of cognitive strategy and exercise setting on running performance, perceived exertion, affect, and satisfaction.
Psychol Sport Exerc. 2004; 5(4): 461–76.
23. MacIntyre TE, Igou ER, Campbell MJ, Moran AP, Matthews J. Metacognition and action: a new pathway to understanding social and cognitive aspects of expertise in sport.
Front Psychol. 2014; 5: 1155.
24. Marcora S. Perception of effort during exercise is independent of afferent feedback from skeletal muscles, heart, and lungs.
J Appl Physiol (1985). 2009; 106: 2060–2.
25. Matthews G, Campbell SE, Falconer S. Assessment of motivational states in performance environments.
Proc Hum Fact Ergon Soc Annu Meet. 2001; 45(13): 906–10.
26. McCormick A, Meijen C, Marcora S. Psychological determinants of whole-body endurance performance.
Sports Med. 2015; 45: 997–1015.
27. Miller EK, Cohen JD. An integrative theory of prefrontal cortex function.
Rev Neurosci. 2001; 24: 167–202.
28. Murias JM, Kowalchuk JM, Paterson DH. Time course and mechanisms of adaptations in cardiorespiratory fitness with endurance training in older and young men.
J Appl Physiol (1985). 2010; 108(3): 621–7.
29. Noakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans: summary and conclusions.
Br J Sports Med. 2005; 39: 120–4.
30. Pageaux B. The psychobiological model of endurance performance: an effort-based decision-making theory to explain self-paced endurance performance.
Sports Med. 2014; 44(9): 1319–20.
31. Renfree A, Martin L, Micklewright D. St Clair Gibson A. Application of decision-making theory to the regulation of muscular work rate during self-paced competitive endurance activity.
Sports Med. 2014; 44(2): 147–58.
32. Schücker L, Knopf C, Strauss B, Hagemann N. An internal focus of attention is not always as bad as its reputation: how specific aspects of internally focused attention do not hinder running efficiency.
J Sport Exerc Psychol. 2014; 36(3): 233–43.
33. Smirmaul BPC, Dantas JL, Nakamura FY. The psychobiological model: a new explanation to intensity regulation and (in)tolerance in endurance exercise.
Rev Bras Educ Fís Esporte. 2013; 27(2): 333–40.
34. Stanley C, Pargman D, Tenenbaum G. The effect of attentional coping strategies on perceived exertion in a cycling task.
J Appl Sport Psychol. 2007; 19(3): 352–63.
35. Suzuki M, Miyai I, Ono T, Kubota K. Activities in the frontal cortex and gait performance are modulated by preparation. An fNIRS study.
Neuroimage. 2008; 39: 600–7.
36. Terry PC, Lane AM, Fogarty GJ. Construct validity of the profile of mood state—adolescents for use with adults.
Psychol Sport Exerc. 2003; 4(2): 125–39.
37. Tucker R. The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance.
Br J Sports Med. 2009; 43: 392–400.
38. Williams EL, Jones HS, Andy Sparks S, Marchant DC, Midgley AW, McNaughton LR. Competitor presence reduces internal attentional focus and improves 16.1 km cycling time trial performance.
J Sci Med Sport. 2015; 18(4): 486–91.
39. Williams EL, Jones HS, Sparks SA, et al. Altered psychological responses to different magnitudes of deception during cycling.
Med Sci Sports Exerc. 2015; 47(11): 2423–30.
40. Woltz DJ, Gardner MK, Kircher JC, Burrow-Sanchez JJ. Relationship between perceived and actual frequency represented by common rating scale labels.
Psychol Assess. 2012; 24(4): 995–1007.
