Affect responses to acute bouts of aerobic exercise: a test of opponent-process theory.

Lochbaum, Marc R. ; Karoly, Paul ; Landers, Daniel M. 等

Research by Thayer, Newman, and McClain (1994) suggests that acute exercise is a highly effective mood-regulating strategy when compared to other common strategies such as passive stimulation (e.g., drinking coffee), and reductions in activity (e.g., watching TV). In addition, acute bouts of aerobic exercise are typically associated with reductions in anxiety and increases in positive mood (Landers & Arent 2001). Hence, it is surprising; in view of this finding and that no one theoretical framework has emerged to consistently explain affective change in response to acute exercise (Landers & Arent, 2001). Several exercise psychology researchers have stated that this lack of a theoretical framework is a result of two phenomenons that have permeated over the last twenty to thirty years of exercise psychology research (Ekkekakis & Petruzzello, 1999; McCann & Holmes, 1984; Tuson & Sinyor, 1993).

The first of these phenomenons was the fact that the major impetus in examining the exercise-affect relationships was to explain the often reported "feel-good" effect reported in the popular press (Tuson & Sinyor, 1993). The second impetus in exercise psychology and affect research was to examine whether exercise could be used as a therapeutic devise in treating affective disorders (McCann & Holmes, 1984). This desire to verify the "feel-good" phenomenon and to examine the viability of exercise as an affective therapy required only descriptive based investigations as opposed to theory based examinations. Likewise, Ekkekakis and Petruzzello (1999) in a review of dose-response exercise and affective investigations also concluded that most of these investigations were descriptive in nature and consider theory based explanations in a post hoc manner. Hence, few strides have been made with regard to systematic examination of theory with regard to the exercise induced affect relationship or the "feel-good" phenomenon. An examination of the extant theoretical perspectives applicable to exercise and mental health suggests that Solomon's opponent-process model of acquired motivation may provide an appropriate guiding framework (Petruzzello, Landers, Hatfield, Kubitz, & Salazar, 1991; Petruzzello, Jones, & Tate, 1997). Solomon's (1980) theory provides a potential explanation for how initially unpleasant experiences, in this case acute aerobic exercise, can eventually result in an acquired positive feeling state for an extended period of time. Because of this acquired positive feeling, enhanced post-exercise affect has been cited as a motive for continued exercise (Hatfield, 1991). Especially pertinent to the present investigation, the theory also predicts that training or prolonged experience with initially aversive activity can result in greater positive feelings after cessation of the activity.

Solomon's (1980) theory proposes that the brain is organized to oppose extreme emotional processes (e.g., pleasure or pain). Such opposition is accomplished by countering an arousing stimulus with an opposing or "opponent" reaction. With the onset of the stimulus, in this case exercise, the organism is said to activated; and this activation is termed the a process. The b or the opponent process is aroused by the a process, and acts to achieve balance or homeostasis by moving the organism toward positive emotionality. Applied to an acute bout of exercise, this formulation offers a reasonable account for why exercise, which can initially be an unpleasant experience due to fatigue, soreness, pain and the like particularly for inactive or unfit individuals, may become a self-reinforcing habit. Within Solomon's framework, affective change is a result of the differences in rates of a and b process initiation and termination (or return to preexisting baseline levels). For instance, the organism undergoes a rapid change (the a process) at stimulus onset, whereas, the b process is delayed and gradually builds in strength until it reaches a peak. Cessation of the original or eliciting stimulus, which results in the complete reduction in the a process, creates a potential for affective change because the b process does not immediately return to baseline levels; thus, an affective state emerges. The resultant affective state is the summation of the two processes (a + b) at any given time. The resultant affective state is also hypothesized to be influenced by the intensity of the initial stimulus because the change in the b process is much more rapid and of greater magnitude at higher intensities. Solomon's theory would therefore predict that a greater magnitude a process would result in a stronger b process and a stronger resultant affective contrast. Solomon's theory likewise proposes that after long-term or repeated exposure to the eliciting stimulus, the a process and the associated affective state (State A) remain relatively constant, while the b process and the associated affective state (State B) become stronger. Such a process model is particularly pertinent to examining the differential emotional consequences of acute exercise because it suggests distinctive affective patterns for trained (physically fit) verses untrained or sedentary participants both during and after physical exertion.

Although researchers have examined many aspects of Solomon's theory (Bixby, Spalding, & Hatfield, 2001; Blanchard, Rodgers, Spence, & Courneya, 2001; Boutcher & Landers, 1988; Steptoe, Kearsely, & Waiters, 1992), only a few have sought to test Solomon's predictions (He, 1998; Petruzzello et al., 1997). Past research using exercise has provided mixed support for Solomon's theory, ostensibly due to methodological limitations. For instance, affect measurement is required prior to, during and post-exercise to adequately test Solomon's theory. Though several researchers cited Solomon's work as potential support for their results (Blanchard et al., 2001; Boutcher & Landers, 1988), none included measurement time points during exercise. In addition, researchers examining Solomon's theory are required to ensure that the two groups of exercisers are distinctly different in aerobic exercise history (i.e., active vs. sedentary). Exercise history is the variable of central importance as conceptualized within an opponent-process framework because any temporal changes in affect due to an acute bout of exercise are should differ as a function of the magnitude of the "b" process that was strengthened due to repeated stimulation or exercise training. However, researchers have not always ensured distinct aerobic fitness differences between participants considered trained and untrained or sedentary (Petruzzello et al., 1997). Nor have they always contrasted a trained group to an untrained or sedentary group (Bixby et al., 2001; He, 1998).

The present study was designed to clarify previous research by addressing the following methodological requirements: inclusion of multiple data collection points during and post-exercise and ensuring exercise history differences between the trained and untrained participants. In addition, the present study sought to extend past research by comparing two different intensities of aerobic exercise. Solomon's (1980) writings suggest that stimulus intensity moderates observed behavior and underlying physiological responses. To date, no one has examined the exercise intensity within a exercise focused investigation meeting the previously discussed requirements for the adequate testing of Solomon's theory. To date, Blanchard et al. (2001) have reported that psychological distress increased from pre to post exercise in unfit subjects in a high intensity exercise condition compared to high fit subjects. No such differences were reported in the low intensity exercise condition. By contrast, Steptoe and colleagues (1992) reported finding no differences between active and inactive participants in two exercise conditions from to pre to post exercise. In the present research the following hypotheses based on Solomon's opponent-process theory of acquired motivation were examined. With regard to intensity, it was hypothesized that greater amounts of positive affect would be reported during recovery in the 70% exercise condition; whereas less positive affect would be reported during the 70% exercise condition when compared to the 55% exercise condition. Second, it was hypothesized that a group by intensity interaction would emerge such that the inactive participants would report lesser amounts of positive affect in the higher intensity condition compared to the active participants. Third, across both participant groups, the temporal pattern of affective reporting will differ during and after exercise in that more negative/less positive affect should be reported during exercise, whereas, more positive/less negative affect should be reported following exercise. Finally, trained participants were hypothesized to report greater levels of positive affect both during and after these two exercise sessions relative to participants who have not engaged in regular cardiovascular exercise (the inactive or untrained group).

Method

Participants

Participants were 53 volunteer, university students (28 active: 15 male, 13 female; 25 inactive: 13 men, 12 women). All participants were recruited via advertisements and personal communications from exercise science and psychology courses at a large southwestern university. The criteria for being classified as an active or trained exerciser involved the frequency, duration, and intensity of the exercise and the duration of training. The American College of Sports Medicine (1998) has recommended 3 to 5 days as the frequency and 15 to 60 minutes as the duration. Intensity requirements tend to vary depending on the duration of training. Pollock and Wilmore (1990) suggested that training differences might occur after a minimal time (e.g., 8 weeks) and duration (e.g., 15 min), but training for a longer duration (> 30 min and > 20 weeks) would result in greater aerobic fitness changes. The criteria we employed for labeling subjects inactive or sedentary were based on detraining data found in Pollock and Wilmore (1990). Because cardiovascular inactivity of greater than eight weeks ensures that the participants' V[O.sub.2max] will be similar to their typical V[O.sub.2max] even if they had been engaged in cardiovascular training prior to current inactivity, participants meeting the inactive criteria in the present study were required to have had no cardiovascular or other type of fitness training for the six months prior to their participation. To be included as an active exerciser in the present study, participants were required to have exercised at least three times per week for 45 minutes at a moderate intensity over the last six months. To assess these requirements, participants completed a physical activity questionnaire without knowledge of the specific requirements for inclusion into the two groups. This questionnaire assessed participants frequency, intensity (Borg, 1985), and duration of aerobic exercise. All active participants had to have met the minimum requirements as described and participants categorized as inactive must have reported no aerobic activity involvement over the last six months.

Measures

Self-reported affect. The Activation Deactivation Adjective Checklist (AD ACL; see Thayer, 1989, Appendix A, pp. 178-180) was used to assess affect. The AD ACL is a 20-item self-report inventory that assesses energetic arousal (EA) and tense arousal (TA). EA and TA are consistent, respectively, with dimensions of positive activation (positive affect) and negative activation (negative affect) in Watson, Wiese, Vaidya, and Tellegen's (1999) model (1). The AD ACL was utilized to derive a measure of positive affect balance (EA - TA). Positive affect balance yields an index of the weight of positive over negative affect (Watson et al., 1988) and is consistent with Solomon's opponent-process theory of acquired motivation (i.e., State A and B). Positive affect balance has been used in past research (Petruzzello et al., 1997) where it has been labeled "affective valence."

The AD ACL was chosen over other measures of affect for several important reasons. First the AD ACL is a theoretically-based modal of activation that is relevant: in an exercise setting. Recently, the problems of measures that do not incorporate activation in an exercise context have been reviewed by Ekkekakis, Hall, and Petruzzello (1999). Second, the AD ACL provides a representation of the global affective space. Finally, the AD ACL's reliability and construct validity are well established (Thayer, 1986). In the present sample, the internal reliabilities for EA and TA were Cronbach alphas were .94, .89, and .90, and .90, 81 to .82, respectively within the three testing days (control, 55% condition, 70% condition).

Maximal Oxygen Consumption (V[O.sub.2max]). V[O.sub.2max] (ml/kg/min) was assessed on the treadmill, and was determined by direct measurement and analysis of expired air samples taken during exercise. A graded exercise protocol (cf., Astrand & Rodahl, 1977) was used to determine each participant's maximal oxygen consumption (an index of aerobic fitness). Active/ trained participants began running/walking at a workload equal to 4 mph, with the workload increased by 1 mph every 3 minutes. Participants wore a nose-clip and a mouthpiece. The VO 2 data were provided by a Vista On-Line system (Rayfield Equipment Ltd, Waitsfield, VT) and the gases were analyzed with a Beckman Oxygen Analyzer OM-I I and a Beckman Medical Gas Analyzer LB-2 (Beckman Coulter Corporation, Kendal, FL). Inactive/untrained participants were similarly assessed. The criterion that indicated attainment of V[O.sub.2max] was a peak or plateau in oxygen consumption with increasing workloads or a respiratory exchange ratio > 1.1 or the attainment of predicted maximum heart rate (i.e., 220 minus age). Heart rate was constantly monitored and recorded with a remote heart watch.

Procedure

Participants were initially asked, via mass screening, whether they met the criteria for being trained or sedentary. Once selected, each participant was required to visit the research laboratory on four separate days over a 10-day period. The first session required the participants to complete the Human Participants Consent Form and a standard health history questionnaire. After completion of these surveys, each participant performed the graded exercise protocol (Astrand & Rodahl, 1977) to determine maximal oxygen consumption On the following test days, participants exercised at the two different intensities with the order determined by random assignment. One condition was a 30 min run at 50-55% of V[O.sub.2max] and the other was a 30 min run at 70-75% of V[O.sub.2max].

On each of these two sessions, self-report affect was collected at time 0 (immediately prior to exercise), at 5, 15, and 25 minutes during exercise, immediately after the termination of the exercise, and finally, at 10 and 20 minutes after the exercise was terminated. Post exercise data collection time points were based on past literature (e.g., Petruzzello et al., 1997) so that direct comparisons could be examined given few investigations has attempted to test Solomon's opponent-process theory of acquired motivation. Self-report affect data were analyzed using a repeated measure ANOVA. In addition, effect sizes were calculated to demonstrate meaningfulness using Hedges (1981) formulas for determining effect size and pooled standard deviation.

Results

Group Differences

As can be seen in Table I, age and height did not differ as a function of group. As a confirmation of the activity classification, a significant main effect emerged for VO[O.sub.2max] such that active participants had a greater V[O.sub.2max] than inactive participants. There was also a significant main effect for weight such that inactive participants weighed more than active participants.

Exercise Manipulation Checks

Paired t-tests were conducted to determine whether intensity, as measured by speed of running (mph) and average heart rate (HR), differed between the 70% and 55% exercise conditions. The speed and heart rate for subjects in the 70% condition (Ms = 5.92 mph + .99 & 164.64 + 15.14 bpm) showed (p < .05) that they were running faster (ES = 1.16) and expending more energy (ES = 1.36) than subjects in the 55% condition (Ms = 4.76 + .71 mph & 143.80 + 15.41 mph). In addition, the speed of running was determined by absolute maximal oxygen consumption. As a result of differences in participants' conditioning level, it was expected that, at the same relative workload (fixed percentage of V[O.sub.2max]), running speed and heart rate would differ between the active and inactive subjects (Pollock & Wilmore, 1990). Consistent with these expectations, both means running speed and heart rate in the 70% condition differed significantly in the predicted direction. Likewise, both means running speed and heart rate in the 55% condition differed significantly (p < .05) between the active and inactive participants and in the predicted direction.

Affect Differences During Exercise

Mean, standard deviations, and within group ESs for the affective balance data are found in Table 1 and 2. To examine our hypothesis concerning exercise intensity interactions with group and time, a 2 (Group) x 2 (Intensity) x 7 (Time) repeated measures ANOVA for affective balance yielded a nonsignificant 3-way interaction (2), F(6,306) = 1.22, p > .05, suggesting that affective balance as reported by the two groups did not significantly interact with the intensity of exercise over time. However, we did obtain significant Intensity by Time, F(6,306) = 8.67, p < .00 I, and Group by Time interactions, F(6,306) = 4.73, p < .001. The Intensity by Time interaction partially supported our hypothesis after inspection of the collapsed group data over time indicated that participants reported greater positive affect during the 55% exercise condition when compared to the 70% exercise condition. No apparent differences emerged during recovery from both exercise conditions. The Group by Time interaction bears most directly on our hypothesis concerning affective responses of the active and inactive groups averaged over both exercise conditions. As can be seen in Figure 1, the significant interaction is a function of the reduction in positive affect balance for the untrained group during the exercise, followed by a slight return to above baseline levels, in contrast, for the active group, positive affect balance increased throughout the exercise bouts and peaked immediately after the cessation of the exercise then began an apparent return to baseline.

[FIGURE 1 OMITTED]

Finally, in support of Solomon's basic premises of group and temporal affective patterns, the main effect for Group, F(1,51) = 6.71, p < .05, and Time, F(6,46) = 5.24, p < .001, were significant. Inspection of the data verified that the active participants, on average, reported greater positive affect balance than did the inactive participants across all exercise time points. As for the temporal pattern, participants reported greater amounts of positive affect balance post exercise compared to during exercise and pre-exercise, though the differences between exercise and recovery were small.

Discussion

The purpose of the present investigation was to examine the viability of Solomon's opponent-process theory of acquired motivation in accounting for differential patterns of positive affect balance after reported between active and inactive participants. First, we examined the predictions that affective responding would interact with exercise intensity, participant group, and time of measurement. Solomon's theory predicts that a low-to-moderate stimulus immediately would elicit a lower level primary (or a) process when compared to a stimulus of greater intensity. Therefore, the opponent (or b) process would also be predicted to be of lesser strength than a b process aroused by a high magnitude primary process. In the present investigation, it was predicted that positive affect balance, especially during recovery from exercise, in the low-to-moderate exercise condition would be less than that of the moderate-to-high stimulus and would interact with the participant group condition and time of measurement. Though the exercise intensities were carefully monitored and differed significantly in average speed and elicited heart rate, we found no evidence for a Group by Intensity interaction.

We did find a significant Group by Time interaction. Examination of the data (see Figure 1 and Table 2), generally, suggested that active participants reported greater positive affect balance during exercise compared to baseline with levels remaining elevated until a gradual descent towards baseline occurred. The inactive participants reported fairly consistent and much lower levels affective balance compared to the active participants both during exercise and recovery from exercise. Because of this fairly consistent difference across time, a significant Group main effect was found as supporting our prediction concerning group difference; that is, that active participants would report more positive affect balance regardless of intensity or time of measurement (expect for baseline). As neither group reported positive affect balance levels that were lower than baseline, the pattern of data do not truly conform to Solomon's theory that requires the stimulus to elicit negative emotions (in this case less positive) compared to a pre-stimulus state.

In addition to our inability to support Solomon's interaction predictions, we did not find a significant difference in affect due to exercise. However, this failure is consistent with a portion of more recent research. For instance, research in the early stages of exercise psychology investigators demonstrated that low-to-moderate intensity exercise did not produce significant affect state change (Morgan, Roberts, & Feinerman, 1971; Sime, 1977). Ekkekakis, Hall, VanLanduyt, and Petruzzello (2000) have commented that these studies were flawed, and their results were subject to speculation. More recently investigators have demonstrated that low-to-moderate walking of much lower intensity than the exercise in the present investigation resulted in affective change similar to that of higher intensity exercise (Ekkekakis et al., 2000; Felts & Vaccaro, 1988; Porcair, Ebbeling, Ward, Freedson, & Rippe, 1989). In addition, the current research is mixed concerning whether affective changes interact with exercise history and exercise intensity (e.g., Blanchard et al., 2001 ; Steptoe et al., 1992) as previously discussed.

As can be seen in Figure 2, the results of the present investigation suggest that exercise intensity interacts with self-reported positive affect during the actual performance of exercise (greater positive affect during the lower intensity exercise). This finding partially supports Solomon's theory. Yet, a closer examination of the data suggests that they support the work of Bixby and colleagues (2001) who examined the interaction of intensity and affect in two distinct (low and high) 30 minute bouts of continuous exercise. These authors framed their investigation by suggesting that self-reported affect in low intensity exercise would follow a maintenance model. A maintenance model states that positive affect or less negative affect is found during the performance of exercise compared to baseline and is maintained during recovery. Conversely, a rebound model was hypothesized to best characterize high intensity exercise. Such a rebound model is similar to that of Solomon's theory in that positive affect is expected to be less negative affect during higher exercise compared to baseline. During recovery affect rebounds (i.e., becomes more positive/less negative). Bixby et al. (2001) did note that this rebound pattern could reverse itself(more positive/less negative during and less positive/ more negative after exercise).

[FIGURE 2 OMITTED]

Examination of the significant Group by Time interaction (Figure 1) in the present study suggested that the active participants' responses averaged across both exercise conditions conformed to Bixby and colleagues' maintenance model. Though positive affect balance began to return to baseline 20 after cessation of exercise, this value was still in the range of scores reported during exercise. The inactive participants' affect balance responses also tended to support the maintenance model though scores were not consistently and significantly elevated above baseline values. It is worth noting that even though the three-way interaction and the two-way Group by Intensity interaction were not significant, it is potentially misleading to suggest that the inactive participants responded similarly to both exercise conditions. The means and the effect size estimates in Table 2 and Figure 3 suggest that the inactive participants' affect reporting between the two conditions varied greatly, whereas, active participants affect reporting was relatively consistent in direction and magnitude. The inactive participants' patterns of positive affect balance in the higher intensity exercise condition (if examined alone) supports Solomon's theory in that exposure to an aversive stimulus results in self-reported aversive feelings states during exercise and a rebound to a more positive state during recovery.

[FIGURE 3 OMITTED]

Just as the active participants' average positive affect balance scores resembled a maintenance model, the averaged scores (see Figure 2) in the 55% exercise condition for both participant groups supported this model. Though the recovery scores at 10 and 20 minutes began to return to baseline, these values remained elevated to the level of positive affect balance during exercise. The temporal pattern for positive affect balance in the 70% condition followed no clear pattern as detailed by Bixby and colleagues (2001). Positive affect balance was elevated during recovery compared to baseline and compared with affect reported near the cessation of the exercise condition. One must remember (see Table 2) that the temporal pattern of the two participant groups varied greatly in the 70% exercise condition, especially during the exercise session.

Limitations and Future Directions

The current failure to find strong support for Solomon's theory may stem from unforeseen methodological failures inherent in the present investigation or simply from the incorrect assumption that exercise holds aversive properties for all participants. One methodological failure might be the timing of post exercise affect. Recent research has begun to suggest a need for a longer post exercise affect measurement time points (Gauvin, Rejeski, & Reboussin, 2000). Gauvin and colleagues (2000) conducted a naturalistic investigation in a community sample of middle-aged women. By using experience-sampling via pager signals, the authors were able to examine affect many hours after exercise termination. The current investigation included post exercise measurement time points similar to those of past investigations that examined Solomon's theory (He, 1998; Petruzzello et al., 1997). Second, Bixby et al. (2001) suggested that past research examining interactions due to exercise intensity have not employed intensities that were homogenous from metabolic requirement across all participants, in the past, researchers had participants exercise at 75% of ventilatory threshold (low intensity exercise) and at ventilatory threshold (high intensity exercise), it could be that the higher intensity condition in the present investigation was not metabolically homogeneous across the two participant groups. Given that the active participants' scores were very similar across all time points (see Table 2), it may be that they perceived the intensities to be very similar even though physiological and running speed differences existed. Though a plausible explanation, it might also be true that the b process is strongly conditioned in active aerobic exercisers. Therefore, exposure to exercise of 55% of V[O.sub.2max] is enough to elicit a strong b process and thus produce a large affective contrast, not only after, but during exercise. Therefore, exercise induced affect will not follow Solomon's predicted pattern (more negative during/more positive after) in participants who engage regularly in aerobic exercise. We did not obtain ratings of perceived exertion which might have assisted us with this shortcoming.

Last, participants were recruited based on aerobic exercise history and not specifically running history. A specificity bias based on mode of training may exist in the current data that have altered the affect balance scores in unknown ways. Berger (1996) has suggested that exercise psychology researchers investigating the exercise-affect relationship should consider personal values and meanings of the physical activity for each participant. Berger (1996) believes based on her summary of past research that the mood benefits of exercise are a result of the following three interacting variables: the participant, the exercise mode/activity including the activity descriptors (i.e., intensity, duration, and frequency), and the exercise environment. Indeed in the present laboratory based investigation, the exercise mode and exercise environment were highly controlled. By asserting such control, the affect pattern of the participants may have been altered. It may be that participants in either group would have preferred swimming or cycling as the exercise mode. Therefore, though difficult to achieve in one investigation, at a minimum future research should examine the exercise-affect relationship within a theoretical framework while attending to the personal meaning of exercise to the participant (i.e., whether they find it enjoyable prior to exercising) and paying special attention to the calculation of exercise intensity.

Table 1

Demographic and exercise parameter means and standard deviations by
participant group

 Active (n = 28) Inactive (n = 25)

 M SD M SD
Descriptive Variables
 Age (yrs.) 24.35 3.54 23.35 3.84
 Weight (kg) (a) 67.39 10.55 80.00 27.30
 Height (cm) 171.60 7.65 173.64 10.02
 VO2max (ml/kg/min) (b) 49.92 5.38 39.30 6.21
Exercise Parameters
 70% condition
 Speed (mph) (c) 6.58 0.71 5.19 0.70
 Heart rate (bpm) (d) 158.36 13.26 171.67 14.19
 55% condition
 Speed (mph) (e) 5.18 0.64 4.30 0.46
 Heart rate (bpm) (f) 138.47 11.53 149.76 17.17

Note: (a) F (1,52) = 44.42, p<.001, ES = -.62; (b) F(1,52) = 44.42,
p<.001, ES = 1.83; (c) t(51) = 7.14, p<.001, ES = 1.98; (d)
t(51)=-3.52, p<.01, ES=-.97; (e) t(51)=5.65,p<.001, ES = 1.78: (f)
t(51)=-2.83, p<.01, ES = -.75.

Table 2

Positive balance means, standard deviation, and effect sizes by the
exercise conditions and participant groups

 Condition

 55%

 Active (n = 28) Inactive (n = 25)

 M SD ES M SD ES

Pre 3.07 4.96 2.88 6.97
During
5 6.89 4.77 0.64 5.60 4.88 .45
15 9.17 4.08 1.02 5.48 6.66 .41
25 9.42 4.22 0.71 5.32 5.80 .41
Post
Immediate 8.60 4.49 0.93 6.20 7.04 .55
10 8.14 5.86 0.85 4.84 7.64 .33
20 7.00 6.00 0.66 4.28 8.47 .23

 Condition

 70%

 Active (n = 28) Inactive (n = 25)

 M SD ES M SD ES

Pre 3.21 5.41 2.92 5.74
During
5 5.64 6.18 0.44 3.68 5.02 .34
15 6.32 5.48 0.56 2.80 6.01 .24
25 7.14 4.61 1.06 0.00 4.61 -.04
Post
Immediate 8.77 6.05 1.00 3.05 6.29 .33
10 8.73 5.92 0.99 3.25 7.72 .22
20 6.99 5.80 0.68 3.83 8.10 .22

Author Note

The paper was based on a dissertation completed by the first author at Arizona State University and was funded by the Douglas L. Conley Memorial Scholarship.

(1) The PANAS was also assessed in the present investigation to establish convergent validity with the AD ACL. Past research (Petruzzello et al., 2001) has referred to the EA and TA components as positive affect and negative affect, respectively. In the present investigation, the PA-NA and EA-TA were strongly related both during and post the 55% exercise condition (r's = .63 and .69) and during recovery (r's = .67 and .68). Given the strong relationships (redundant information) and stated rationale for the utilizing the AD ACL, only the AD ACL data were presented.

(2) The purpose of the control condition was to determine whether the exercise sessions elicited affective properties beyond that of a sit-and-read activity. A 2 (Group) x 3 (Intensity) x 7 (Time) repeated measures ANOVA for affective balance yielded a significant 3-way interaction, F(12,40) = 4.02, p < .01, Wilks' E = .45. This significant three-way interaction was followed up by separate 3 (Intensity) by 7 (Time) interactions for each participant group. Both of these interactions were significant (p < .05), F(12,16) = 3.31, Wilks' E = .29, F(12,13) = 3.20, Wilks' E = .25, for the active and inactive participants, respectively. Inspection of the means (available from the first author) indicated that the exercise session elicited greater positive affect balance especially during the recovery.

References

American College of Sports Medicine (1998). Guidelines for exercise testing and prescription (5th Ed.). Philadelphia: Williams & Wilkins.

Astrand, P., & Rodahl, K. (1977). Textbook of work physiology: Physiological bases of exercise (pp. 331-361). NY: McGraw-Hill.

Berger, B. G. (! 996). Psychological benefits of an active lifestyle: What we know and what we need to know. Quest, 48, 330-353.

Bixby, W. R., Spalding, T. W., & Hatfield, B. D. (2001). Temporal dynamics and dimensional specificity of the affective response to exercise and varying intensity: Differing path ways to a common outcome. Journal of Sport and Exercise Psychology, 23, 171-190.

Blanchard, C. M., Rodgers, W. M., Spence, J., & Courneya, K. S. (2001). Feeling state response to acute exercise of high and low intensity. Journal of Science and Medicine in Sport, 4, 30-38.

Boutcher, S. H., & Landers, D. M. (1988). The effects of vigorous exercise on anxiety, heart rate, and alpha activity of runners and nonrunners. Psychophysiology, 25, 696-702.

Borg, G. (1985). An introduction to Borg's RPE-Scale. Ithaca, NY: Movement Productions.

Ekkekakis, P., Hall, E. E., VanLanduyt, L. M., & Petruzzello, S. J. (2000). Walking in (affective)circles: Can short walks enhance affect? Journal of Behavioral Medicine, 23, 245-275.

Ekkekakis, P., Hall, E. E., & Petruzzello, S. J. (1999). Measuring state anxiety in the context of acute exercise using the state anxiety inventory: An attempt to resolve the brouhaha. Journal of Sport & Exercise Psychology, 21,205-229.

Felts, W. M., & Vaccaro, P. (1988). The effect of aerobic exercise on post-exercise state anxiety and psychophysiological arousal as a function of fitness level. Clinical Kinesiology, 42, 89-96.

Gauvin, L., Rejeski, W. J., & Reboussin, B. A. (2000). Contributions of acute bouts of vigorous physical activity to explaining diurnal variations in feeling states in active, middle-aged women. Health Psychology, 19, 365-375.

Hatfield, B. D. (1991). Exercise and mental health: The mechanisms of exercise-induced psychological states. In L. Diamant (Ed.), Psychology of sports, exercise and fitness (pp. 17-49). New York: Hemisphere.

He, C. (1998). Acute exercise of varying intensities and durations in fit and unfit subjects." Its effects on mood states and electroencephalograph activity. Unpublished doctoral dissertation, Arizona State University, Tempe.

Hedges, L. V. (1981). Distribution theory for Glass's estimator of effect size and relatedestimators. Journal of Educational Statistics, 6, 107-128.

Landers, D. M. & Arent, S. (2001). Physical activity and mental health. In R. Singer, H. A.

Hausenblas, & C. M. Janelle (Eds.), Handbook of Sport Psychology (pp. 740-765). New York: John Wiley & Sons, Inc.

McCann, I. L., & Holmes, D. S. (1984). Influence of aerobic exercise on depression. Journal of Personality and Social Psychology, 46, 1142-1147.

Morgan, W. P., Roberts, J. A., & Feinerman, A. D. (1971). Psychologic effect of acute physical activity. Archives of Physiological Medicine and Rehabilitation, 52, 422-425.

Petruzzello, S. J., Jones, A. C., & Tate, A. K. (1997). Affective responses to acute exercise: A test of opponent-process theory. Journal of Sports Medicine and Physical Fitness, 37,205-212.

Petruzzello, S. J., Landers, D. M., Hatfield, B. D., Kubitz, K. A., & Salazar, W. (1991). A meta-analysis on the anxiety reducing effects of acute and chronic exercise. Sports Medicine, 11, 143-182.

Pollock, M. L., & Wilmore, J. H. (1990). Exercise in health and disease. Philadelphia: W. B. Saunders.

Porcari, J. P., Ebbeling, C. B., Ward, A., Freedson, P. S., & Rippe, J. M. (1989). Walking for exercise testing and training. Sports Medicine, 8, 189-200.

Sime, W. E. (1977). A comparison of exercise and meditation in reducing physiological response to stress. Medicine and Science in Sports, 9, 55.

Solomon, R. L. (1980). The opponent-process theory of acquired motivation: The costs of pleasure and the benefits of pain. American Psychologist, 35, 691-712.

Steptoe, A., Kearsley, N., & Walters, N. (1992). Acute mood responses to maximal and submaximal exercise in active and inactive men. Psychology and Health, 8, 89-99.

Thayer, R. E. (1986). Activation-deactivation adjective check list: Current overview and structural analysis. Psychological Reports, 8, 607-614.

Thayer, R. E. (1989). The biopsychology of mood and arousal. Oxford: Oxford Press.

Thayer, R. E., Newman, R., & McClain, T. M. (1994). Self-regulating of mood: Strategies for changing a bad mood, raising energy, and reducing tension. Journal of Personality and Social Psychology, 67, 910-925.

Tuson, K. M., & Sinyor, D. (1993). On affective benefits of acute aerobic exercise: Taking stock after twenty years of research. In P. Seraganian (Ed.), Exercise psychology: The influence of physical exercise on psychological processes (pp. 271-360). New York: Academic Press.

Watson, D., Wiese, D., Vaidya, J., & Tellegen, A. (1999). The two general activation systems of affect: Structural findings, evolutionary considerations, and psychobiological evidence. Journal of Personality and Social Psychology, 76, 820-838.

Paul Karoly

Daniel M. Landers

Arizona State University

Address Correspondence To: Marc Lochbaum, Department of Health, Exercise, and Sport Sciences, Exercise Science Center, Box 43011, Lubbock, TX 79409-3011. Phone: 806-742-3371, Fax: 806-742-1688, Email: Marc.Lochbaum@ttu.edu