JOURNAL OF

SPORT EXERCISE PSYCHOLOGY

Journal of Sport & Exercise Psychology, 2014, 36, 506-515 http://dx.doi.org/10.1123/jsep.2014-0029 © 2014 Human Kinetics, Inc.

Official Journal of NASPSPA

www.JSEP-Journal.com ORIGINAL RESEARCH

The Effect of Ego Depletion on Sprint Start Reaction Time Chris Englert1 and Alex Bertrams2 1University

of Heidelberg; 2University of Mannheim

In the current study, we consider that optimal sprint start performance requires the self-control of responses. Therefore, start performance should depend on athletes’ self-control strength. We assumed that momentary depletion of self-control strength (ego depletion) would either speed up or slow down the initiation of a sprint start, where an initiation that was sped up would carry the increased risk of a false start. Applying a mixed between- (depletion vs. nondepletion) and within- (before vs. after manipulation of depletion) subjects design, we tested the start reaction times of 37 sport students. We found that participants’ start reaction times decelerated after finishing a depleting task, whereas it remained constant in the nondepletion condition. These results indicate that sprint start performance can be impaired by unrelated preceding actions that lower momentary self-control strength. We discuss practical implications in terms of optimizing sprint starts and related overall sprint performance. Keywords: ego depletion, reaction time, self-control, self-regulation, sport, sprint In sprints in track and field, an optimal sprint start is of central significance because a few tenths of a second can be decisive for finishing first or second in a competition (e.g., Gough, 2006; Pilianidis, Kasabalis, Mantzouranis, & Mavvidis, 2012; Santana, 2000). According to Harland and Steele (1997), the sprint start in a 100-m sprint accounts for approximately 5% of the total race time. Therefore, to succeed, athletes need to initiate their movements as soon as possible and accelerate as quickly as possible after receiving the starting signal (e.g., Brown & Vescovi, 2012). Sometimes, however, athletes display suboptimal start reaction times or false starts (Ditroilo & Kilding, 2004). The International Association of Athletics Federations (IAAF) set a false start criterion in sprints; namely, that start reaction times from the onset of the starting signal to movement initiation under 100 ms have to be considered a false start. It is assumed that athletes displaying reaction times beneath this threshold initiated their movement before the onset of the shot and, thus, speculated and anticipated when the starting signal would appear. As one can become disqualified after a false start, sprinters aim to initiate their movement as closely as Chris Englert is with the Department of Sport Psychology, Institute of Sports and Sports Sciences, University of Heidelberg, Heidelberg, Germany. Alex Bertrams is with the Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany. Address author correspondence to Chris Englert at christoph.englert@issw. uni-heidelberg.de.

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possible to the 100 ms threshold to potentially gain an advantage while at the same time avoiding a false start and disqualification (Collet, 1999). During the sprint start procedure (more precisely, from the “set” command until starting the run after the starting signal), an athlete therefore needs to consecutively exhibit two different main responses. The first is not to move forward between the “set” command and the starting signal in order not to become disqualified due to a false start; the second is to initiate the sprinting action as fast as possible immediately after hearing the starting signal. To succeed, an athlete has to shift from the first to the second response within milliseconds. There are different ways to improve overall sprint performance by focusing on the sprint as a whole, including the start, acceleration, and top-end speed (e.g., Behrens & Simonson, 2011; McFarlane, 1993). In the current study, we assume a good start is essential for sprint peak performance (e.g., Gough, 2006; Santana, 2000), especially in sprints up to 100 m (Collet, 1999). We examine under which circumstances athletes are capable of optimally reacting to a starting signal and when they are likely to perform suboptimal sprint starts. For this reason, we link sprint starts to momentarily available self-control resources. As we will argue below, an optimal sprint start may be a self-regulatory act that requires self-control strength.

Self-Control Strength and Its Depletion Volitionally inhibiting or altering a response can be considered a self-control act (e.g., Baumeister, Heatherton, &

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Tice, 1994). The strength model of self-control (e.g., Baumeister, Bratslavsky, Muraven, & Tice, 1998; Muraven & Baumeister, 2000) proposes that all self-control acts are energized by the same resource, a metaphorical strength with limited capacity. According to the strength model, a primary act of self-control can deplete one’s self-control strength for some time, which does not immediately become replenished. During this timeframe, termed ego depletion, subsequent self-control acts cannot be executed as efficiently as before, leading to performance impairments in further self-control actions (e.g., Baumeister et al., 1994). This theoretical assumption has received considerable empirical support: Several studies have shown that ego-depleted participants performed worse in tasks requiring impulse regulation (e.g., Friese, Hofmann, & Wänke, 2008), emotion regulation (e.g., Bertrams, Englert, & Dickhäuser, 2010; Englert & Bertrams, 2013b), attention regulation (e.g., Englert & Bertrams, 2013a; Schmeichel & Baumeister, 2010), or complex cognitive operations (e.g., Bertrams, Englert, Dickhäuser, & Baumeister, 2013). In a recent meta-analysis, Hagger and colleagues (Hagger, Wood, Stiff, & Chatzisarantis, 2010a) found a medium-to-large effect of ego depletion on subsequent self-control acts. Several theoretical considerations have been made with respect to the processes underlying ego depletion. Challenging the notion of limited self-control strength, it has been argued that the observed ego depletion effects are explainable by resource allocation (Beedie & Lane, 2012), motivational and attentional shifts (Inzlicht & Schmeichel, 2012), cost/benefit computations (Kurzban, Duckworth, Kable, & Myers, 2013), or subjective theories about the limitation of willpower (Job, Dweck, & Walton, 2010). However, recent empirical work that has taken into account such motivational explanations of ego depletion have found evidence in favor of the limited self-control strength model (Vohs, Baumeister, & Schmeichel, 2012; in the context of physical performance: Graham, Bray, & Martin Ginis, 2014). While the discussion on in-depth processes is ongoing, there is little doubt that initial self-control demands impair self-control in subsequent unrelated tasks (see the meta-analysis of Hagger et al., 2010a). In the present research, we refer to the strength model of self-control because presently it has the most established status in terms of explaining ego depletion effects. Recently, researchers have begun to transfer the strength model of self-control to the field of sport psychology (e.g., Englert & Bertrams, 2012; Furley, Bertrams, Englert, & Delphia, 2013; Graham et al., 2014; Hagger, Wood, Stiff, & Chatzisarantis, 2010b; Martin Ginis & Bray, 2010; McEwan, Martin Ginis, & Bray, 2013). A finding of high relevance for sport psychology has been provided by Dorris, Power, and Kenefick (2012). These authors found that ego depletion induced by an unrelated complex cognitive task lowered subsequent performance in athletes’ physical exercise routines. Thus, ego depletion apparently can impair execution of athletic tasks that had been well practiced and frequently performed.

The Role of Self-Control Strength for the Sprint Start The aim of the current study was to examine whether and how ego depletion affects the speed of sprint starts. Theoretically, two contradictory options can be argued in this regard: Ego depletion could either increase or decrease sprint start reaction times. We will first point out why one could assume that ego depletion accelerates sprint starts, and then explain why it may also be possible that starting reaction times become slower in the state of ego depletion. As previously mentioned, the sprint starting procedure as a whole involves two successively required main responses: first, not to move too early (i.e., between “set” command and starting signal), and second, to accelerate as quickly as possible (i.e., immediately after the starting signal). Between these two responses lies the starting signal, which indicates the moment in which the athlete has to switch as fast as possible from the first required response (i.e., standing still) to the second required response (i.e., quickly moving forward). We think that during the starting procedure, athletes have to control one of two possible predominant response tendencies, each conflicting with the response actually required at the moment. While they must wait in the set position, athletes could have a strong inclination to initiate movement because they aim to finish the race in first place (Collet, 1999). It might therefore be that while awaiting the start signal, athletes have to inhibit the predominant response of running toward the finish line; that is, they have to exert self-control. Previous ego depletion research has demonstrated that recent self-control demands can impair the subsequent inhibition of impulsive responses in nonmotor behavior (Friese et al., 2008; Hofmann, Rauch, & Gawronski, 2007). Furthermore, the depletion effect has been applied to impaired inhibition of motor responses. For instance, when initial self-control is depleted compared with a nondepleted state, people are less likely to inhibit the urge to relax their hand muscles while squeezing a handgrip (Graham et al., 2014; Muraven, Tice, & Baumeister, 1998). In a study by Finkel et al. (2006), depleted persons were apparently less able to inhibit undesired hand and arm movements during a dexterity task. More specifically related to starting responses, McEwan and colleagues (2013) recently found that depleted participants displayed significantly more false-start errors in a dart throwing task. Such motor behavior is distinct from the movement required during sprint starts. It may, however, function as indirect evidence that depleted compared with nondepleted sprinters may start faster because their ability to inhibit the predominant motor response of running ahead is reduced. This would frequently be an advantage, but would also carry a higher risk of false starts and corresponding disqualification. A contrary possibility is that athletes are predominantly inclined to keep still rather than to initiate movement between “set” and starting signal. This response

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tendency would be plausible as well because sprinters need to avoid a false start (and the disqualification it means) at any cost. If so, after the starting signal, sprinters would have to exert self-control in the form of quickly overriding the strong inclination to not move and promptly replacing it by a movement response. Ego depletion would impair such self-control and consequently make the sprint start slower than it would be in a nondepleted state, thereby harming the athlete’s overall sprint performance. Indirect evidence for this assumption can be seen in studies that found initial self-control demands to increase reaction times (measured in milliseconds) in those trials of subsequent Stroop tasks that required quick overriding of a response (i.e., self-control; Richeson & Shelton, 2003; Richeson & Trawalter, 2005). In these trials, individuals had to replace a predominant response (i.e., indicating the semantic meaning of a color word such as BLUE) as quickly as possible with a different response (i.e., indicating the noncorresponding color in which the color word was depicted). Further evidence more close to motor behavior stems from Baumeister et al. (1998). These authors found that depleted individuals initiated movement later than did individuals who were not depleted. Specifically, after initial self-regulatory effort compared with noneffort, it took participants longer to press a button for quitting a boring task. An interpretation of this finding would be that depleted persons compared with nondepleted persons more readily remain in the state of, and are less able to actively alter, their momentary nonmovement. However, the kind of movement in this previous study is rather different from the movement in the sprint start situation.

Present Research No study conducted so far has directly examined ego depletion with respect to sprint starts. As previous research does not provide us with direct references, it is hard to predict which of the two alternative effects of ego depletion—speeding up or slowing down the starting reaction time—is actually at work during sprint starts. From our view, both alternatives can plausibly be argued from the base of ego depletion research. Therefore, we tested whether ego depletion affects sprint start reaction times at all, and if so, which of the two contrary possibilities gains empirical support. For the current study, we hence hypothesized that sprint start reaction times change from before to after an unrelated self-control demand that depletes athletes’ self-control strength; however, we did not predict in which direction the reaction times would change (i.e., whether they decrease or increase). Whatever direction the change takes, it should be more pronounced in comparison with a nondepleted control group whose self-control strength is relatively intact. To investigate our prediction, we applied a mixed between-/within-subjects design. As a between factor, the participating sprinters were randomly assigned to either a depletion condition or a nondepletion condition. This experimental manipulation of momentary self-control

strength took place as an intermediate task between two sets of sprint starts. As a within factor, the athletes performed the two sets of three maximum-speed 10-m sprints each, and we measured participants’ average reaction times to initiate the sprint movement. As the first set of sprints (T1) took place before the manipulation of selfcontrol strength, we did not expect statistically significant differences between the two experimental conditions. The second set of sprints (T2) took place after the manipulation of self-control strength. According to our prediction, participants’ average reaction times in the depletion condition should change from T1 (i.e., with intact self-control strength) to T2 (i.e., with depleted self-control strength) relative to the nondepleted control group.

Method Participants We conducted our study with N = 37 sport students (Mage = 22.05, SDage = 1.89; 13 females) with sprint experience in track and field events (i.e., 100- to 400-m sprint and hurdle; experience: M = 4.07 years, SD = 3.91) who volunteered to participate in our study. In their meta-analysis, Hagger and colleagues (2010a) reported a medium-tolarge effect for ego depletion on self-control dependent measures (i.e., d = 0.62). Our sample was large enough to find an effect of this size (G*Power analysis with α = .05 and 1 – β = .80; Faul, Erdfelder, Lang, & Buchner, 2007). All participants were healthy and uninjured, and did not perform any high-intensity training before starting the experimental procedure. Participants were randomly assigned to either the depletion condition (n = 18) or the nondepletion condition (n = 19). Before starting the experimental procedure, we obtained written informed consent from each participant.

Materials and Procedure We conducted our study in an indoor track and field facility with a rubberized surface in single sessions, with each session taking approximately 20 min per participant. Overall scores for all questionnaires applied in the current study were calculated by averaging each participant’s answers on the respective measure. Higher scores on the specific questionnaire always indicated higher values of the corresponding variable. Participants reported demographic information (e.g., age, sex, track and field experience in years, sprint experience in years). We wanted to make sure that there were no statistically significant differences in trait sports anxiety between the two experimental conditions because trait anxiety can have an influence on action initiation (e.g., Krane & Williams, 1994). Therefore, participants completed the German version (WAI-T; Brand, Ehrlenspiel, & Graf, 2009) of the Sport Anxiety Scale-2 (SAS-2; Smith, Smoll, Cumming, & Grossbard, 2006), which contains 12 items. They answered the items on 4-point Likert-type scales ranging from 1 (not at all) to 4 (very

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much) in regard to how they generally feel before or during sporting competitions. The three subscales of the WAI-T are each comprised of four items: Worry (e.g., “I worry that I will not play well”; α = .84), somatic (e.g., “My body feels tense”; α = .75), and concentration (e.g., “It is hard to concentrate”; α = .81). Then, after a 5- to 10-min individual warm-up phase, we instructed participants to perform three 10-m maximal effort sprints at T1 (see Haugen, Tønnessen, & Seiler, 2012). We considered that three starts would ensure sufficient reliability on the one hand, and would not be too exhausting on the other hand. After each sprint, participants received approximately 90 s of rest to recover (Frost, Cronin, & Levin, 2008). To measure participants’ reaction times, we placed a foot-pressure release system under the starting block (for this procedure, see Haugen et al., 2012). For that cause, we used a Brower Timing System (Brower, Salt Lake City, UT), which can measure reaction times accurately within milliseconds. Participants were in the starting block waiting for the acoustic starting signal to be given by the Brower Timing System as we followed the commands of the International Association of Athletics Federations (IAAF). The timeframe between “set” and the start signal was 3–4 s and was randomly chosen for each sprint. We used this flexible timeframe to minimize the possibility that athletes could count down to the starting signal. There was a wireless device connected to the foot-pressure release system which measured the time (in milliseconds) from the starting signal to the point when the pressure from the front foot against the foot-pressure release system was removed (Brower, Salt Lake City, UT). We applied this method because the reliability of real-time notations and manual video-based analyses are, in large part, dependent on observer skills and observer objectivity (Carling, Bloomfield, Nelsen, & Reilly, 2008; Hetzler, Stickley, Lundquist, & Kimura, 2008). We followed the false start criterion recommended by the IAAF (2013); that is, reaction times below 100 ms were regarded as a false start. Next, we administered a transcription task that has been successfully applied in previous research to experimentally manipulate momentary self-control strength (e.g., Bertrams et al., 2013; Englert & Bertrams, 2012; Wolff, Baumgarten, & Brand, 2013). Participants were instructed to transcribe on a separate sheet of paper for 6 min a neutral text that did not contain any emotion-arousing words. In the depletion condition, the instruction was to always leave out the letters e and n while transcribing the text. Transcribing text this way depletes self-control strength because individuals have to volitionally override their habitual writing habits (i.e., exertion of self-control; cf. Muraven, Gagné, & Rosman, 2008; Schmeichel, 2007) when performing the task. In the nondepletion condition, participants transcribed the text conventionally, which did not require self-control strength. Therefore, in the nondepletion condition, participants’ self-control strength should have remained intact. Afterward, the participants completed a four-item manipulation check (e.g., “How strongly did you have to

regulate your writing habits,” “How effortful did you find the writing task”; α = .68) adapted from previous research (e.g., Furley et al., 2013). This measure served to assess whether our manipulation of ego depletion was successful in the current study. We also included an item to assess whether the transcription task had any unintended effects on perceived self-efficacy (“How successful do you think you performed in the transcription task?”). Items were answered on 4-point Likert-type scales from 1 (not at all) to 4 (very much). As another manipulation check, we also counted the number of transcribed words and the number of mistakes while performing the transcription task. Considering that the instructions in the depletion condition were more difficult to follow and that participants had to override well-elaborated writing habits, we expected that participants from the depletion condition would transcribe fewer words and make more mistakes compared with the nondepletion condition in which the text was simply transcribed conventionally. Then, participants completed the German Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988; German: Krohne, Egloff, Kohlmann, & Tausch, 1996) because we wanted to analyze whether our experimental manipulation of self-control strength had any unintended effects on momentary affect. Within the PANAS, 10 items—including items on attentiveness, joviality, and self-assurance—assess positive affect (e.g., alert, excited, proud; α = .79) and 10 items—including items on anxiety, guilt, hostility, and sadness—assess negative affect (e.g., nervous, ashamed, angry, distressed; α = .61). All items were answered on 4-point Likert-type scales from 1 (not at all) to 4 (very much). Next, at T2, participants performed another set of three 10-m maximal effort sprints. We again measured their reaction times with the foot-pressure release system under the starting block (Brower, Salt Lake City, UT). The setup, the measurements, and the instructions were identical to those used at T1. After finishing the experimental procedure, participants were thanked for their participation, probed for suspicion, and given a debriefing about the content of our study.

Results Preliminary Analyses Table 1 provides descriptive statistics for the following analyses. The two experimental conditions did not differ in any of the three aspects of sport anxiety, ps > .37 (independent samples t tests). Thus, findings may be independent of preexperimental differences in the tendency to worry, to feel somatic arousal, or to having difficulties concentrating. Moreover, an independent samples t test showed that there were no preexperimental differences between the two experimental conditions in average start reaction times at T1, p = .42, indicating that randomization was successful with regard to starting ability. Furthermore, our experimental manipulation of momentarily available self-control strength was successful

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Table 1  Descriptive Statistics: Means and Standard Deviations Experimental Condition Depletion Variable WAI-T somatic WAI-T worry WAI-T concentration Manipulation check PANAS positive PANAS negative Number of transcribed words Number of mistakes Reaction time T1 Reaction time T2

M 1.97 1.72 1.75 2.35 2.74 1.34 98.61 11.44 350 377

SD 0.45 0.48 0.65 0.45 0.48 0.27 24.88 6.41 37 44

Nondepletion M 1.82 1.75 1.58 1.76 2.37 1.21 129.74 1.68 360 354

SD 0.46 0.60 0.49 0.44 0.62 0.27 22.39 1.29 43 39

Note. n = 18 in depletion condition; n = 19 in nondepletion condition. Overall scores of a psychometric scale were obtained by averaging the responses to the scale items. WAI-T = Wettkampfängstlichkeitsinventar (German version of the Sports Anxiety Scale, SAS-2). PANAS positive = German version of the Positive and Negative Affect Schedule–positive affect. PANAS negative = German version of the Positive and Negative Affect Schedule–negative affect. Reaction time T1 = average reaction time (in milliseconds) out of three 10-m maximal effort sprints at first time of measurement. Reaction time T2 = average reaction time (in milliseconds) out of three 10-m maximal effort sprints at second time of measurement.

in the current study because participants from the depletion condition had statistically significantly higher scores on the manipulation check compared with participants from the nondepletion condition, t(35) = 3.95, p < .001, d = 1.33 (independent samples t test). Moreover, participants from the depletion condition transcribed fewer words compared with the nondepletion condition, t(35) = –4.01, p < .001, d = –1.32. In the same vein, participants from the depletion condition made significantly more mistakes than participants from the nondepletion condition, t(35) = 6.50, p < .001, d = 2.11. The participants from the depletion condition followed our instructions as no participant from the depletion condition transcribed the text conventionally. In addition, the transcription task did not have any unintended effects on perceived self-efficacy, on positive affect or on negative affect, ps > .14 (independent samples t tests). Therefore, effects of the experimental manipulation may not alternatively be attributed to differences in self-efficacy or affect. The coefficient of variation (CV) for the three measures of reaction times was 12% each at T1 and at T2, which can be considered as low (cf. Lovie, 2005). Therefore, the three measures of each time of measurement could be averaged. False starts did not occur at T1 or at T2, and were thus not examined.

Main Analyses To test our assumption that momentarily available selfcontrol strength affects reaction times in sprint starts, we conducted a 2 × 2 mixed between-/within-subjects analysis of variance (ANOVA). Experimental condition (ego depletion vs. nondepletion) was the between-subjects factor, time of measurement (T1 [before the depletion

manipulation] vs. T2 [after the depletion manipulation]) was the within-subjects factor, and average start reaction time was the dependent variable. In line with our prediction, there was a significant interaction between the manipulation of self-control strength and time of measurement, F(1, 35) = 6.00, p = .02, η2p = .15, indicating that start reaction time changed from T1 to T2 depending on the experimental condition. Participants’ performance from the depletion condition decreased statistically significantly from T1 (M = 350, SD = 37) to T2 (M = 377, SD = 44), F(1, 35) = 7.62, p = .01, η2p = .18, which can be considered a large effect (Cohen, 1988). In contrast, in the nondepletion condition participants’ performance did not differ statistically significantly between T1 (M = 360, SD = 43) and T2 (M = 354, SD = 39), F(1, 35) = 0.46, p = .50, η2p = .01.1 Thus, when self-control strength was still intact, starting performance did not suffer from T1 to T2.

Discussion In the current study we investigated the assumption that ego depletion affects sprint start performance. We considered two contrary effects of ego depletion on start reaction time as theoretically possible; that is, either an acceleration of the start (involving a heightened potential risk of false starts) or a deceleration of the start (implying suboptimal performance). As expected, we found that the depletion of momentary self-control strength had an effect on sprint start reaction times. Participants’ average start reaction time increased from a first measurement with fully available self-control strength to a second measurement with depleted self-control strength; that is, the participating athletes started slower than they

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actually could after their self-control strength was no longer fully available. In contrast, start reaction times did not differ between our two times of measurement for participants whose self-control strength was intact during both times. This means that the athletes showed starting performance at their usual levels constantly over time when their self-control strength was not depleted by an unrelated interim task. Overall these findings are in line with the notion that athletes have a strong inclination not to move between “set” and starting signal, which has to be promptly overridden in an act of self-control as soon as the starting signal occurs. How fast athletes accomplish this shift depends on their momentary self-control strength—a very limited and exhaustible resource (Baumeister et al., 1998). Our results are not compatible with considering sprint starts as simple reaction tasks that do not involve self-control at all. If so, there should have been no effect of ego depletion on starting reaction times. Furthermore, our findings do not support the view that sprint starts would require self-control in the form of inhibiting a strong impulse to start the movement before the starting signal. In this case, we should have found accelerated start reaction times, or even false starts, in depleted sprinters. In this regard, however, the present results differ from previous research reporting that ego depletion can impair the inhibition of motor responses (e.g., Graham et al., 2014; McEwan et al., 2013). The inconsistency between studies may be explained by differences in the principal regulatory demands. McEwan et al. (2013), for instance, found that depleted participants who had just established a habit to throw darts only when a green cue light flashed became prone to “false starts” after the rule had changed to not throw when the light turns green. In this study, the most prepotent self-regulatory demand may have been to restrain from responding to the original starting signal (green light). Depleted participants were less able to accomplish such self-control and, hence, were more likely to start movement too fast, or at the wrong moment, respectively. In our study, by contrast, no novel starting signal was imposed to which the participants had to adapt. We assume that the crucial self-regulatory demand for our participants was to quickly overcome the inclination to keep still (based in the motivation to avoid a false start) and to immediately replace it with acceleration. When they were depleted, participants became less successful at this self-regulatory act, and therefore their starting reaction times slowed down. On a general level, we think that to predict in which way ego depletion impacts motor responses, the kind of self-regulatory demands that the specific situation primarily imposes on the individual must be taken into account. The present findings implicate that sufficient levels of self-control strength enable athletes to initiate their sprint movements more efficiently. High availability of self-control strength may therefore give athletes an important advantage in sprints in which a few tenths of a second can be decisive for winning or losing a competition (e.g., Gough, 2006; Harland & Steele, 1997; Pilianidis et al.,

2012; Santana, 2000). In our experiment, the difference in start reaction times before and after the depletion of selfcontrol strength was large, according to Cohen’s (1988) classification. Still, the difference was only measureable in milliseconds. One should keep in mind, however, that this effect emerged after only 6 min of engaging in selfregulatory effort in physically recovered athletes. We assume that in crucial competitions, athletes’ self-control strength may be frequently taxed by multiple demands. For instance, athletes during a competition have to cope with fatigue, pain, stress, and distractions (e.g., Gaudreau, Blondin, & Lapierre, 2002), which should cost them a good deal of self-control strength (Muraven & Baumeister, 2000). Therefore, we consider the present findings to point to self-control strength as a relevant performance determinant in sprint competitions. In spite of the strengths of the study, limitations should also be addressed. The transcription task we applied to experimentally manipulate self-control strength has been successfully used in previous selfcontrol research (e.g., Bertrams et al., 2013; Englert & Bertrams, 2012; Wolff et al., 2013); however, it is not sport specific. Considering that thus far no sport-specific depletion tasks have been developed, we chose this established manipulation for the current study. Hagger and colleagues (2010a) found empirical support in their meta-analysis that self-control strength is not domain specific, meaning that there should have been a carry-over effect of ego depletion caused by the transcription task on self-control during the starting procedure. Further support for this assumption comes from recent work by Bray, Graham, Martin Ginis, and Hicks (2012), who found that a depleting cognitive task impaired subsequent physical performance. The transcription task can be seen as a proxy of the various self-regulatory demands—related and unrelated to sports—that athletes face before and during competitions or training units, and which can affect their sport performances. A benefit of the transcription task is that the participants in the current study were not familiar with this task, making it unlikely that there were any preexperimental differences between our two experimental conditions based on practice effects. Another potential limitation relates to our manipulation check. We estimated via various indicators (i.e., items on difficulty, effort, and degree of overriding a habit; number of words transcribed and mistakes made) how much self-control had been invested during the transcription task and used it to infer differences in ego depletion between the two experimental groups. The use of engagement in self-control as a manipulation check for ego depletion is based on theory and empirical findings that both recent self-control and ego depletion are conceptually and empirically closely connected (for a recent meta-analysis, see Hagger et al., 2010a). One could argue that only assessing the self-regulatory demands of the manipulation task alone may not be a proper manipulation check, as it would not provide direct information on between-participants variance in depletion. However, directly measuring how much depletion occurred may

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be hard to achieve. Asking participants how depleted, fatigued, or tired they feel, for instance, has not revealed differences between depletion and control groups in some relevant studies that demonstrated ego depletion effects (e.g., McEwan et al., 2013; Martin Ginis & Bray, 2010; see also Baumeister, Gailliot, DeWall, & Oaten, 2006; Vohs, Glass, Maddox, & Markman, 2011). This suggests that ego depletion is primarily a behavioral phenomenon rather than a subjective experience. Future research should still seek to clarify the relationship between behavioral and affective aspects of ego depletion by adding refined measures of depletion (e.g., implicit methods) as manipulation checks. We must also note that we did not apply a full battery of checks on the depletion manipulation task (e.g., on how unpleasant, frustrating, and important the task was for the participants; on the participants’ investment in working the task; and on how the participants perceived the consequences of making mistakes). Such measures may be useful to distinguish the effects of depletion from the ones of other motivational or affective variables. We did not find differences between the experimental conditions in ratings of global positive and negative affect and on perceived success in the transcription task. Even though there were differences in the number of words transcribed and mistakes made in the transcription task (indicating differences in the exertion of self-control), depleted participants were not in a worse mood and did not feel less successful than their nondepleted counterparts. Based on these findings and on the results of previous studies using the same or very similar manipulations (e.g., Bertrams et al., 2013; Englert & Bertrams, 2012; Schmeichel, 2007; Wolff et al., 2013), we conclude that the transcription task actually led to ego depletion rather than to unpleasantness, frustration, or awareness of failure in the depletion condition while keeping self-control intact in the nondepletion condition. Nonetheless, future research should apply a more elaborate manipulation check to make sure that the transcription task actually serves as a task to manipulate self-control strength instead of other unintended processes. Another limitation is that we measured starting times with a foot-pressure release system that we placed under the starting block. Although this method seems superior to more subjective measures, such as real-time notations and manual video-based analyses (Carling et al., 2008), several researchers have argued that time recordings largely depend on the applied instrument (e.g., Duthie, Pyne, Ross, Livingstone, & Hooper, 2006; Haugen et al., 2012). Therefore, future studies should also try to replicate our findings by applying real-time notations and manual video-based analyses to rule out potential unintended influences of the assessment tool. According to Gough (2006), a sprint can be broken down into three separate parts, namely, start, acceleration, and top-end speed. In our study, we solely investigated the influence of momentarily available self-control strength on the start. In future studies, researchers should additionally investigate the role of self-control strength

on acceleration and top-end speed, which was beyond the scope of the current study. Here, we were interested in finding initial evidence that the sprint start procedure involves self-control, as well as whether and how reduced self-control resources impair the sprint start. As previously mentioned, there is an ongoing debate about the mechanisms underlying the ego depletion effect, at which some authors call the notion of limited self-control strength into question (e.g., Beedie & Lane, 2012; Graham et al., 2014; Job et al., 2010; Kurzban et al., 2013; Vohs et al., 2012). The examination of alternative explanations to the strength model was outside the scope of the present research. However, future research that looks deeper at the psychological processes during sprint starts may benefit from recent theorizing in this regard. For instance, Job and colleagues (2010) found that an individual’s subjective theory about the exhaustibility of willpower has an influence on self-control. In their studies, individuals who considered willpower as a limited and exhaustible resource showed the typical ego depletion effect, but there was no carryover effect of a primary self-control task on subsequent self-control in individuals who believed in unlimited willpower. It may therefore be that the effect we found was based on the sprinters’ implicit beliefs in the exhaustibility of their self-regulatory powers rather than on depleted selfcontrol strength. Vohs et al. (2012) replicated Job et al.’s (2010) finding, but, in support of the strength model, they also found that after extensive self-control effort, ego depletion occurred even in people who viewed willpower as an unlimited resource. This indicates that two or more parallel processes may contribute to the ego depletion effect and that in future research, moderator variables (e.g., extent of initial self-control effort) should be taken into account to fully understand the self-regulatory processes during sprint starts. The findings of this study may have considerable practical implications. According to the strength model of self-control on the one hand, self-control strength can become depleted after exerting self-control, but on the other hand, its availability can also be improved by training. Repeatedly, it has been demonstrated that exerting self-control regularly over a 2-week period can reduce proneness to ego depletion (see Baumeister, Gailliot, DeWall, & Oaten, 2006). In addition, Tyler and Burns (2008) showed that depleted self-control strength can be replenished by active relaxation. Implementing self-control training into the daily training routines and learning strategies for the purpose of quick replenishment during sporting competitions could improve athletes’ sprint start performance.

Note 1. Analysis of covariance (ANCOVA) constitutes an alternative way to analyze the effect of an experimental manipulation on changes in a variable (Van Breukelen, 2006). Applying ANCOVA revealed results corresponding to the ones obtained

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with the mixed between-/within-subjects ANOVA. As expected, both experimental groups differed in reaction times at T2 when reaction times at T1 were held constant, F(1, 34) = 5.24, p = .03, η2p = .13. A comparison of the adjusted means demonstrated that ego depletion slowed the starting response down (depletion condition: Madjusted = 380, SE = 9; nondepletion condition: Madjusted = 351, SE = 9).

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