International Journal of Applied Sports Sciences 2007, Vol. 19, No. 1, 86-95. ⓒ Korea Institute of Sport Science
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect Mária Rendia, Attila Szabob,c, & Tamás Szabóa,
b
Faculty of Physical Education and Sport Sciences, Semmelweis Universitya, National Institute for Sport Talent Care and sports Servicesb, Faculty of Natural Science, University of Pécsc, Hungary Twenty healthy young women participated in thislaboratory research. They completed the Exercise Induced Inventory (EFI - Gauvin & Rejeski, 1993) before, immediately after, and 15-mins after a 20-minute progressive treadmill exercise during which they ran for 5-mins at 50%, 60%, 70% and 80% of their maximal heart rate reserve (MHRR). Before, during every stage of exercise, and twice after exercise, the participants were asked to continuously identify a letter in a specific position in unexpected words – presented in 8 second intervals over a period of three minutes – while their information processing speed (IPS) was gauged. Results showed that IPS was shortest when participants ran at 80% of MHRR, suggesting that quick mental choices are made easier under heightened levels of arousal. No changes in affect (transient mood states) from pre- to post-exercise were seen. These findings appear to support the circumplex model of affect claiming that affective valence is invariant (unchanged) when distracting mental tasks are undertaken during exercise. key words: Affect, Circumplex model, Cognitive processing, Exercise intensity, Information processing
Introduction1) Cognitive performance during acute bouts of physical activity has been studied extensively (Brisswalter, Collardeau, & Arcelin, 2002). The over 200 papers
Received : 22 March 2007, Accepted : 19 June 2007 Correspondence : Attila Szabo(
[email protected])
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect 87
published in this field since 1930 may still project controversial findings. This apparent controversy is primarily due to inconsistent methods used in terms of type of cognitive challenge and exercise characteristics. The examination of cognitive performance during physical activity has important practical implication on "correct" decision making in open skills such as teamsports. Therefore, the nature of cognitive tasksshould be similar to the nature of the task the athletes are facing in game situations where fast, correct decisions are needed. Cognitive tasks requiring fast and correct decisions from several alternatives are known as choice reaction time (CRT) tasks. For several decades it was postulated that the speed of cognitive responses to CRT tasks follows an "inverted-U"pattern during increasing exercise intensity protocols (Davey, 1973). Specifically, it was held that cognitive performance increases up to a certain level of moderate workload, but as the workload increases furthercognitive performance deteriorates. McMorris & Graydon (2000) have presented a thorough and systematic review on the impact of incremental exercise on cognitive performance and have concluded that there is little or no evidence for the inverted-U hypothesis. However, their review also hints that in those studies in which a CRT task was used a moderate workload yielded faster responses in contrast to rest (control) or high intensity exercise. Nevertheless, in two of their studies in a series McMorris and Graydon found that adopting a decision making task in soccer at maximum power output exercise was faster than at a submaximal workload. The accuracy of responses was unaffected by varying the exercise intensity in these studies. It appears then that the typeof the cognitive task may also influence observed effects. Indeed, recent empirical evidence demonstrates that simple reaction time tasks, where information processing is virtually absent, is unaffected by incremental exercise whereas CRT is faster at40%,60% and 80% of maximal aerobic power than at rest or at 20% of maximal aerobic power (Mouelhi Guizani et al., 2006). Further task characteristics that may influence the results in this area of research may be task-complexity, familiarity with the task, and mode of presentation. Research also shows that acute aerobic exercise induces positive momentary feeling states, known as affect (Ekkekakis & Petruzzello, 1999). Such effects are almost universal, but the mechanisms triggering these effects are not fully understood. Several physiological models were proposed including the endorphin hypothesis, the amine hypothesis (Dunn & Dishman, 1991), and the thermogenic hypothesis (Koltyn, 1997). However, it is dubious that any of these models is
88 M. Rendi et al.
indeed responsible for post exercise changes in affect, because passive activities like listening to music or low-exertion physical activities like tai-chi and yoga have resulted in positive affective benefits identical to that of aerobic exercise (Szabo et. al., 1998). Also,acute bouts of team-sports do not yield positive changes in affect (Szabo & Bak, 1999) that would be expected to occur if the exercise-induced affect has physiological origins. The possible explanation is that some psychological processes including distraction, enjoyment, anticipation or expectation, or a combination of these is responsible primarily for changes in affect. If these psychological processes are absent, due to cognitive and attentional processes during team sports for example, the affective benefits may also be absent. In this laboratory research a within-participants repeated measures design was used to assess cognitive performance at rest, during four stages of incremental exercise workload, and twice following exercise while alsousing an exercise-specific instrument for measuring affect before and after exercise. It was proposed that cognitive performance will follow an inverted-U pattern vis-à-vis incremental exercise intensity and that exercise-induced changes in affect would be masked by the cognitive task, similar to team-sport situations.
Methods Participants Participants were recruited from among Sport Science students at a large urban university. Twenty healthy Caucasian women (age = 20.6, SD ± 1.6 years) volunteered for the research and consented to participation. Their mean weight was 61.6 kg (SD ± 6.4), mean height was 164.8 cm (SD ± 5.4), and they exercised regularly 4.3 times per week (SD ± 1.4) or for an average of 6.8 hours per week (SD ± 2.8). Accordingly, they were habituated to exercise.
Materials The Exercise-Induced Feeling Inventory (EFI - Gauvin & Rejeski, 1993) was used to measure affect before and after exercise. The EFI is a 12-item questionnaire containing four subscales. The 12 items are rated on a five-point scale, ranging
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect 89
from zero (do not feel at all) to four (feel very strongly), the degree to which they experience four affective states: positive engagement (enthusiastic, upbeat, happy), revitalization (energetic, refreshed, revived), tranquillity (calm, peaceful, relaxed), and physical exhaustion (fatigued, tired, worn out). The affective states are claimed to be conceptually (and psychometrically) distinct. For example, positive engagement gauges the degree of enjoyment of exercise, revitalization measures how refreshed the person feels after exercising, tranquillity reflects the state of post-exercise calmnessassociated with a bout of exercise, finally physical exhaustion gauges the mental appraisal of fatigue resulting from exercise (Gauvin &Rejeski, 1993). The EFI was presented with very good psychometric properties (Bozoian et al., 1994). The internal consistencies of the four subscales ranged from .72 to .91 (Gauvin & Rejeski, 1993). Nevertheless, more recently, the EFI has been criticised (Ekkekakis & Petruzzello, 2000, 2001), but the developers have defended the instrument with credible and reliable arguments (Gauvin & Rejeski, 2001). The cognitive task employed in this study consisted of a "letter-in-a-word" task. This task required participants to identify a letter in the 4th, 5th or 6th position in a given word. For example, the 4th letter in "worldwide" called for the answer "L." An equal number of letter positions were presented at all stages of exercise and rest in a counterbalanced (mixed) order. It was conjectured that unlike some other cognitive tasks, like mental arithmetic, this type of task would not be biased by mathematical skills or experience. The task was presented via a portable cassette player and the answers provided by the participants were tape-recorded for subsequent analyses of information processing speed (IPS) as well as accuracy. Within test stability (consistency) of this task was studied in a pilot study with a sample comparable to the participants in the current research. Pilot work showed that under resting conditions this type of task yields similar results that are not significantly different from one trial to another, thus the dilemma of practice or habituation may not be present in at least the first ten trials.
Procedure After arrival atthe laboratory, participants completed the Exercise Induced Inventory (EFI - Gauvin & Rejeski, 1993). Following a five-minute rest period, baseline heart rate was measured using a Polar heart rate monitor that was attached tothe chest of the participant by a female experimenter for subsequent monitoring of the heart rate-based exercise intensities. Heart rate obtained at rest was used to
90 M. Rendi et al.
determine the maximal heart rate reserve (MHRR) of the participant in accord with the classical Karvonen formula (Karvonen et al., 1957). After obtaining the baseline heart rate, participants have performed the first cognitive task (at rest) trial. The task was presented via an audio cassette player and the answers provided by the participants were tape recorded for subsequent analysis of the information processing speed (IPS) as well as accuracy, defined as the percentage of correct answers. A new word was presented at every eight (8) seconds for a total of three minutes in each experimental stage. After completion of the EFI and the cognitive task at rest, participants wereready for exercise. There were four stages of progressive exercise: 50%, 60%, 70% and 80% of the participants’MHRR. Each stage lasted for five minutes while the elevationof the treadmill was adjusted continuously at a constant speed to ensure that participants reach the projected workload before the elapse of the five-minute interval. In the last three minutes of each stage of exercise participants completed the cognitive task. The exercise session was followed by a 15-minute rest period. In the first two minutes following exercise, participants completed the EFI and then also completed the cognitive task. The same action was repeated 15 minutes after exercise.
Results A multivariate repeated measures analysis of variance (MRM-ANOVA), using the subscales of the EFI as the four dependent measures, was used in the first instance to examine whether changes in affect (momentary or transient mood states) have taken place. However, the results of this analysis were statistically not Table 1. Means and standard deviation for the four subscales of the EFI before and after exercise and 15 minutes after exercise. No statistically significant differences were found between pre- and post-exercise periods. Measure
Pre-exercise
Post-exercise
15-min Post-exercise
Mean
SD
Mean
SD
Mean
SD
Positive Engagement
5.75
1.55
5.95
2.31
5.80
2.04
Revitalisation
4.65
2.06
4.85
2.72
5.3
2.34
Tranquillity
6.20
1.85
6.05
2.21
6.50
1.70
Exhaustion
3.60
2.85
4.60
2.66
3.30
2.05
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect 91
significant (Wilks’ Lambda = .837, F (8, 70) = 0.814, p > .05; see Table 1). Repeated measures analysis of variance, using Greenhouse-Geisser correction for the degrees of freedom yielded a statistically significant ‘period’ effect (see Figure 1) for the IPS (F(4.1, 77.8) = 4.59, p< .002). This main effect was followed up using Bonferroni adjusted pairwise comparisons that is an option (in the SPSS statistical software program) to repeated measures ANOVA. These comparisons indicated that the IPS was shorter at 70% and 80% than at 50% MHRR (p < .05). Further, the IPS at 80% MHRR was shorter than at the 15 minutes post-exercise period (p < .05). Finally, as revealed through another repeated measures ANOVA by adopting the Greenhouse-Geisser correction for the degrees of freedom no statistically significant differences have emerged in information processing accuracy or the percentage of correct answers (F (4.5, 86.1) = 1.84, p > .05).
Figure 1. Information processing speed in the various phases of the exercise protocol. The values on the Y axis represent the IPS or the choice reaction times (CRT) in seconds. Pre = before exercise; Post1 = immediately after exercise; Post2 = 15-minutes after exercise.
Discussion and Conclusion There are two key findings emerging from this research. The first, which is in
92 M. Rendi et al.
line with the extant literature, shows that information processing speed (IPS) tends to decrease as exercise intensity increases. Indeed, for decisional tasks such as the task used in the current inquiry performance may be expected to decrease (Brisswalter et al., 2002). Studies using increasing workloads or a progressive exercise protocol suggest that the optimal workload for increased cognitive performance ranged between 40% and 60% of the participants VO2max. However, matching the finding in the current research, significant increases in cognitive performance were also recorded at higher workloads in well trained individuals (Brisswalter et al., 2002; Mouelhi Guizani et al., 2006). Regardless whether the status of training or the complexity of the decision making aspect of the mental task is responsible for such findings, it appears that the inverted-U argument may not account for cognitive performance during exercise at increasing workloads. These results then strengthen the conclusion reached by McMorris and Graydon (2000) that there is little or no support for an inverted-U effect of incremental or progressively harder exercise on cognitive performance. Based on the current findings, in which the fasted IPS was seen at the highest exercise workload, it may be suggested that the "drive theory" could also providean explanation. Indeed, mental performance may be linearly linked to exercise intensity in case of skill-neutral or simple tasks, but not so for perceptual or more complex decisional tasks. In the latter case the inverted-U theory may be still applicable. In a sporting situation this finding may be appealing, because it suggeststhat at high exercise intensities some simple choices are done faster than at rest. The second important findingemerging from this lab research is that affect did not change significantly from pre- to post-exercise. There are two explanationsfor this finding. The first is that positive affective changes are masked after progressive exercise. Yet sound support for this contention may not exist especially if considering the findings that affective changes did not emerge even 15 mins after the exercise session. Indeed post-exercise values (refer to Table 1) were nearly identical to pre-exercise values. Recent evidence suggests that in incremental exercise protocols affect becomes more negative at higher exercise intensities (Acevedo et al., 2007). However, in the current study it is unlikely that such negative changes have occurred because the first post-exercise measurement of affect has occurred within the first two minutes immediately after completing the 80% MHRR exercise stage. The second and more plausible explanation may be that cognitive processing interfered with some psychological processes responsible for the induction of
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect 93
positive affect in a similar manner like in team sports (Szabo & Bak, 1999). In light of a popular circumplex model of affect(Russell, 1980) the affective valence may be invariant when a distracting mental task is undertaken during exercise. The simple explanation of such invariance rests with the fact that when the brain is processing information as the bulk of brain activity it processes emotions via lesser neural connections. This conjecture is based on the "connectionistic"model (Rumelhart & McClelland, 1986), which is consistent with the levels-of-processing approach in that the more connections to a single idea or concept, the more likely it is to be remembered and vice versa. Accordingly, if the physiological models alone could explain post-exercise positive changes in affect, then such changes would occur after progressive exercise as well regardless of cognitive focus during exercise. Accordingly, it appears that psychological processes (that may be traced to the Circumplex model) are in part responsible for post-exercise affect. However, if these psychological processes are distracted by cognitive performance like the continuous information processing in team sport, the expected positive changes in affect remain masked. These results, albeit sounding speculative, are important in the understanding of the exercise-affect relationship and, therefore, they deserve future empirical attention. While the finding with respect to cognitive performance and affect-mediating effect of exercise are consistent with the reports in the relevant literature (i.e., McMorris & Graydon, 2000; Szabo & Bak, 1999) there are some notesof caution that should be kept in perspective while evaluating the implication of the current findings. First, although the current study was a within-participant design in which the participants act as their own control, the lack of an exercise control group for the cognitive task and an exercise without cognitive task control group for affective changes may be a valid criticism. The first control group is needed to ascertain that habituation does not take place (even though the response at 15 minutes post-exercise do not seem to suggest that habituation may have taken place –refer to Figure 1). The second control group may be required to ensure that the lack of change in affect is indeed due to the cognitive intervention and not merely to adaptation or preoccupationwith effort and fatigue during increases in exercise workload. Another critique may be related to the uniqueness of the participants in this study who were young and physically active women whose responses may be different from older, male, or sedentary samples. Finally, in this inquiry the highest workload was 80% MHRR and, thus, it is remains unknown whether cognitive performance would further improve at maximal power output or at 100% of the
94 M. Rendi et al.
MHRR. In spite of the above listed plausible criticisms, based on the results of this research it may be concluded that information processing speed (IPS) on a relatively simple and skill-independent cognitive task gets shorter as the exercise workload increases. Further, again consistent with McMorris and Graydon (2000), response accuracy is unaffected by exercise workload. Finally, while there were no improvements in affect from pre- to post-exercise, in contrast to Acevedo et al.’s (2007) findings, no negative changes in affect have taken place.
References Acevedo, E. O., Kraemer, R. R., Kamimori, G. H., Durand, R. J., Johnson, L. G., & Castracane, V. D. (2007). Stress hormones, effort sense, and perceptions of stress during incremental exercise: an exploratory investigation. Journal of Strength & Conditioning Research, 21, 283-289. Bozoian, S., Rejeski, W. J., & McAuley, E. (1994). Self-efficacy influences feeling states associated with acute exercise. Journal of Sport and Exercise Psychology, 16, 326-333. Brisswalter, J., Collardeau, M., & Arcelin, R. (2002). Effects of acute physical exercise characteristics on cognitive performance. Sports Medicine, 32, 555-566. Davey, C. P. (1973). Physical exertion and mental performance. Ergonomics, 16, 595-599. Dunn, A. L., & Dishman, R. K. (1991). Exercise and the neurobiology of depression. Exercise and Sport Sciences Reviews, 19, 41-98. Ekkekakis, P., & Petruzzello, S. J. (2001). Analysis of the affect measurement conundrum in exercise psychology: II. A conceptual and methodological critique of the Exercise-induced Feeling Inventory. Psychology of Sport and Exercise, 2, 1-26. Ekkekakis, P., & Petruzzello, S. J. (2000). Analysis of the affect measurement conundrum in exercise psychology: I. Fundamental issues. Psychology of Sport and Exercise, 1, 71-88. Ekkekakis, P., & Petruzzello, S. J. (1999). Acute aerobic exercise and affect: Current status, problems and prospects regarding dose-response. Sports Medicine, 28, 337-374. Gauvin, L., & Rejeski, W. J. (2001). Disentangling substance from rhetoric: a rebuttal to Ekkekakis and Petruzello (2001). Psychology of Sport and Exercise, 2, 73-88. Gauvin, L., & Rejeski, W. J. (1993). The Exercise-Induced Feeling inventory: development and initial validation. Journal of Sport and Exercise Psychology, 15, 403-423. Karvonen, M., Kentala, K., & O. Mustala, O. (1957). The effects of training heart rate: a longitudinal study. Annales Medicinae Experimentalis et Biologiae Fenniae 35, 307-315. Koltyn, K. F. (1997). The thermogenic hypothesis. In W. P. Morgan (Ed.). Physical activity and
Relationship between Physical Exercise Workload, Information Processing Speed, and Affect 95
mental health (pp. 213-226). Washington: Taylor & Francis. McMorris, T., & Graydon, J. (2000). The effect of incremental exercise on cognitive performance. International Journal of Sport Psychology, 31, 66-81. Mouelhi Guizani, S., Bouzaouach, I., Tennenbaum, G. Ben Kheder, A., Feki, Y., & Bouaziz, M. (2006). Simple and choice reaction times under varying levels of physical load in high skilled fencers. Journal of Sports Medicine & Physical Fitness, 46, 344-351. Rumelhart, D., & McClelland, J. (Eds.). (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Cambridge, MA: MIT Press. Russell, J. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 29, 1161-1178. Szabo, A., & Bak, M. (1999) Exercise-induced affect during training & competition in collegiate soccer players. European Yearbook of Sport Psychology, 3, 91-104. Szabo, A., Meskó, A., Caputo, A., & Gill, E. (1998). Examination of exercise-induced feeling states in four modes of exercise. International Journal of Sport Psychology, 29, 376-390.
