JOURNAL OF SPORT & EXERCISE PSYCHOLOGY, 1994,16,326-333 O 1994 Human Kinetics Publishers, Inc.

Self-Efficacy Influences Feeling States Associated With Acute Exercise

Shannon Bozoian W. Jack Rejeski University of Illinois at Urbana-Champaign Wake Forest University

Edward McAuley University of Illinois at Urbana-Champaign

The present study examined the role that preexisting efficacy cognitions played in the generation of exercise-induced feeling states during and follow- ing an acute bout of exercise. In so doing, the construct validity of a newly developed measure of psychological responses to exercise, the Exercise- Induced Feeling Inventory (EFI; Gauvin & Rejeski, 1993), was investigated. Female undergraduates, classified as having either high or low physical efficacy, engaged in an acute exercise bout and feeling states were recorded prior to, during, and following the activity. More efficacious females main- tained a sense of energy during exercise and felt more revitalized and experi- enced increased positive engagement postexercise than did their less efficacious counterparts. Such findings provide further support for a social- cognitive interpretation of how psychological responses to physical activity might be generated. Results are further discussed in terms of the measurement of exercise-induced feeling states and future applications of the EFI.

Key words: exercise-induced feeling states, well-being, perceived control

Regular participation in exercise and physical activity is suggested to result in both physiological and psychological health benefits. Reported physiological benefits include reductions in cardiovascular disease and decreased prevalence of other related coronary risk factors, such as hypertension and obesity (Blair et al., 1989). Psychological benefits reported from exercise participation typically include reductions in anxiety (Landers & Petruzzello, 1994) and enhanced psycho- logical well-being (McAuley, 1994). However, studies of exercise effects on psychological responses have rarely been grounded within a theoretical frame- work. Moreover, there are those who argue that there are problems with existing

Shannon Bozoian and Edward McAuley are with the Department of Kinesiology at the University of Illinois at Urbana-Champaign, Louise Freer Hall, Urbana, IL 61801. W. Jack Rejeski is with the Department of Health and Sport Science at Wake Forest University, 307 Reynolds Gym, Box 7234, Winston-Salem, NC 27109.

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approaches to the measurement of psychological responses within the context of exercise, particularly acute bouts of work (e.g. Gauvin & Rejeski, 1993; McAuley & Courneya, 1994).

Several underlying processes have been identified as possible links between exercise and improved mental health, including physiological (e-g., thermogenic effects) or biochemical (e.g., endorphins) mechanisms (Morgan, 1985). From a social-psychological perspective, several researchers have alluded to the potential role played by perceptions of mastery (e.g., Morgan, 1985). Social cognitive theory (Bandura, 1986) suggests that self-efficacy expectations influence affect, and some initial reports in the exercise literature provide evidence to support such a contention. For example, McAuley and Courneya (1992) reported that more efficacious older adults reported more positive affect during graded exercise testing than did individuals with lower self-efficacy. Additionally, McAuley (1991) examined the influence of previous exercise participation, self-efficacy, and causal attributions on affective responses of middle-aged males and females engaged in a 20-week exercise program. Not only did efficacy expectations influence positive affective responses to exercise participation directly, but they also had an indirect effect through personally controllable attributions. Thus, the degree to which individuals perceive themselves to have some control or mastery over the environment appears linked to the valence of affective responses experi- enced.

In general, researchers in this domain have been content to employ measures of affect that have neither been developed for nor adequately validated in the exercise domain. In an effort to provide a measurement technology that allows researchers to more fully explore those changes associated with acute exercise participation, Gauvin and Rejeski (1993) developed the Exercise-Induced Feeling Inventory (EFI). This multidimensional measure taps four distinct feeling states: revitalization, tranquility, positive engagement, and physical exhaustion. Al- though the positive dimensions of the EFI are moderately correlated, Gauvin and Rejeski (1993) presented initial reliability and validity information to suggest that the EFI is a multidimensional measure possessing adequate psychometric properties. For example, the four-factor structure has been confirmed across samples, appears to be sensitive to the stimulus properties of the exercise setting, and shares expected variation with related constructs that are typically employed to assess emotional responses to exercise (Gauvin & Rejeski, 1993).

The present study was designed to examine several conceptual issues in the context of relatively unfit college females. First, we attempted to further examine the validity of the EFI in a controlled laboratory setting. Second, we explored the hypothesis that perceptions of efficacy may influence feeling states experienced as a function of an exercise stimulus. As such, we were interested not simply in assessing feeling states at a single point in time but in determining how efficacy expectations were related to these responses over the course of the exercise bout. For example, one might hypothesize that if efficacy is related to more positive subjective responses, then those subjects with greater efficacy would be expected to demonstrate significantly greater increases from preexercise through in-task measurement to posttask assessment. That is, such feelings as revitalization, tranquility, and positive engagement should be enhanced over time more so in those subjects with a stronger sense of their physical capabilities. On the other hand, it would be hypothesized that although both high and low efficacy

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subjects should report increased physical exhaustion over the exercise period, this exhaustion should be less marked in the high efficacy group.

Method

Subject Characteristics

Female undergraduate students (N = 36, M age = 18 years, SD = .075) were recruited as subjects for this study. Based on self-efficacy scores (described below) subjects were classified as either high or low physical efficacy participants. Biometric data (M + SE) indicated that there were no significant differences between high and low efficacy subjects on either weight (high efficacy M = 60.5 f 2.58 kg; low efficacy M = 57 + 1.76 kg) or estimated V0,max (high efficacy M = 36.6 f 1.68 mlkglmin; low efficacy M = 40.11 +_ 1.65 mlkglmin. Further- more, analysis of self-reported daily exercise habits for the previous 2 months revealed that on average the low efficacy group spent as much time on vigorous aerobic exercise as the high efficacy group (-1.50 hr per week).

Measures

Self-Efficacy. The self-efficacy scale used in the present study was a general aerobic exercise efficacy scale. Subjects were asked to rate their confi- dence toward exercising at 70% of their maximum capacity in 5-min increments beginning with a bout of 5 min and ending with a bout that was 45 min in duration. All subjects had personal experience with exercising at target heart rates from their participation in a university required health and fitness course. For each item, subjects indicated their degree of confidence on a 0-100 scale (0 = no confidence at all; 50 = moderately confident; 100 = complete confidence). Inspection of subject responses on this measure indicated that the median physical efficacy for this task was 50. Therefore, subjects scoring below the median were classified as low efficacy and those above the median as high efficacy.

Estimated Aerobic Capacity. The A s t r a n d - ~ h ~ m i n ~ Cycle Ergometer Test (Wstrand & Rhyming, 1954), a submaximal protocol, was employed to estimate V02max. The equipment used for this test included a Monark cycle ergometer (Model #868) and a Lifepack 5 ECG Cardiac MonitorIRecorder. During the 6-min test, subjects pedaled at a cadence of 50 revlmin with the workload set between 450 and 900 kpms depending on the subject's age, body size, and perceived level of aerobic fitness. Throughout the test, heart rates ( M s ) were recorded during the last 10 s of each minute and were stable ( 4 beats per minute difference) throughout the final 2 min of the test with a target HR of between 120-170 beats per minute. The average HR and workload during the last 2 min were then used to predict maximal oxygen consumption, an estimate of aerobic fitness level.

Ratings of Perceived Exertion (RPE). General RPEs were determined via the Borg scale (1985). This instrument consists of numerical values ranging from 6 to 20 with modifiers (e.g., 7 = very, very light; 12 = somewhat hard; 19 = very, very hard) following each odd integer. Test-retest reliabilities of .80 and higher have been reported, and numerous studies have attested to its validity for assessing perceived work intensity (Borg, 1985).

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Feeling States. The Exercise-Induced Feeling Inventory (Em, Gauvin & Rejeski, 1993) was employed to assess feeling states prior to, during, and follow- ing the acute exercise bout. As previously noted, the EFI is a 12-item, four- dimensional measure intended to tap feelings of tranquility, revitalization, positive engagement, and physical exhaustion. Subjects in this study were asked to indicate on a 0 (do not feel) to 4 (feel very strongly) point scale the degree to which they were currently experiencing each item. Internal consistency for each scale was adequate, as indicated by coefficient alpha of .76 for Tranquility, .82 for Revital- ization, .74 for Positive Engagement, and .85 for Physical Exhaustion.

Procedures

Subjects reported to a human performance laboratory where they first completed an informed consent, were weighed on a balance scale, had their height measured using a steel tape, and completed a 2-month recall of weekly physical activity. Subsequently, they were instrumented with a five-lead electro- cardiogram, rested quietly for 5 min to determine resting heart rate, and then completed the self-efficacy measure and the EFI scale in counterbalanced format. Following these assessments, subjects were prepared for an exercise test on a cycle ergometer that involved a 7-min warm-up followed by 20 min of exercise at 70% of heart rate reserve (HRR). Using the Karvonnen (1957) formula, the 70% level was determined by using a maximal heart rate of 220 minus age for all subjects.

During the 7-min warm-up, V02max was estimated using the Astrand- Rhyming procedure described previously. Upon termination of this test, subjects continued to exercise so that the workload could be adjusted for the 20-min bout to be completed at 70% HRR (taking a total time of about 1 min). During this 20-min bout of exercise, heart rates and RPEs were recorded every 5 min. Additionally, at the 15-min mark, the EFI was once again administered with subjects orally indicating the degree to which each feeling state was being experi- enced. Finally, following exercise, subjects rested quietly in a chair for 10 min and then completed the EFI for a third time.

Results and Disucssion

Table 1 provides the descriptive statistics for the individual cells of a 2 (high efficacy vs. low efficacy) x 3 (preexercise, during exercise, and post- exercise) mixed model MANOVA in which the subscale scores of the EFI served as dependent variables. This analysis yielded a significant multivariate interaction term, F(8, 130) = 2.77, p < .01. Univariate follow-up analyses demonstrated that positive engagement, F(2, 68) = 8.84, p < .01, and revitalization, F(2, 68) = 8.84, p < .01, were responsible for this multivariate effect. Simple main effect analyses and painvise contrasts with a Bonfenoni adjustment revealed that sub- jects high in self-efficacy experienced an increase in positive engagement post- exercise (p < .05), whereas feelings of positive engagement for the low self- efficacy group decreased from preexercise level (p < .05).

Interestingly, subjects with low self-efficacy experienced a decline in revi- talization during exercise, which returned to preexercise levels within a few

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Table 1 Means and Standard Errors for EFI Scores by Self-Efficacy Grouping

Self-efficacy grouping

Time of High efficacy Low efficacy El3 subscale assessment M SE M SE

Positive engagement Before exercise During exercise After exercise

Revitalization Before exercise During exercise After exercise

Tranquility Before exercise During exercise After exercise

Fatigue Before exercise During exercise After exercise

Note. For Positive Engagement and Revitalization, means not sharing a common super- script differ from one another at p < .O1 level of significance.

minutes postexercise (see Table 1). By contrast, subjects with high self-efficacy maintained their preexercise levels of revitalization during activity and experi- enced a significant increase postexercise, a value that was substantially higher than the group with low self-efficacy (see Table 1). All subjects experienced a decline in tranquility during exercise, from a mean ( f SE) of 7.05 ( k 0.39) to 5.61 (M.48), and an increase in physical exhaustion, from 3.88 (H.51) to 6.00 (39.51). Responses to these feeling states recovered to preexercise levels within 10 min following activity with postexercise tranquility score increasing to 7.58 (M.49) and physical exhaustion dropping to 3.38 (H .40) , F(2, 68) = 15.35, p < .01, for tranquility, and F(2, 68) = 14.00, p < .01, for physical exhaustion.

It should be noted that physiological and subjective exertion responses indicated that both efficacy groups were working at similar levels. At the 15- min mark of exercise, there were no significant differences in RPE; low efficacy group mean (f SE) was 14.38 ( f .42), whereas the high efficacy group mean was 14.11 (k.35). Furthermore, the heart rate data for both groups at this point in time were essentially identical: low efficacy mean (k SE) was 168.94 (f 1.38), whereas the high efficacy group mean was 169.66 (k1.54).

As has been noted elsewhere (cf. McAuley & Courneya, 1992), the exercise psychology literature has generally ignored the role played by subjective states during physical activity, choosing to focus primarily on the overall affective influence of self-reported chronic activity. Moreover, the ability of most instru- ments employed to assess the effects of exercise on feeling states has been suspect. Additionally, the relationship between the exercise stimulus and subjec- tive responses has been examined largely from a descriptive perspective with

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little theoretical reasoning guiding hypotheses. We attempted to address each of the above concerns in the present study by examining the role that preexisting efficacy cognitions (~andukt, 1986) in the of exercise-induced feeling states during and following an acute exercise bout. In so doing, we sought to further determine the construct validity of the EFI (Gauvin & Rejeski, 1993).

Bandura (1986) proposed that efficacy expectations antedate affect, and there is some support for such a contention in both the clinical (e.g., Cutrona & Troutman, 1986) and exercise psychology literature (e-g., McAuley, 1991; McAuley & Courneya, 1992). Our results parallel the findings of these studies in that more efficacious females experienced greater positive feeling states during and following exercise than did their less efficacious counterparts. Specifically, the more efficacious group maintained a sense of energy and revitalization during

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exercise and felt more revitalized postactivity. In sharp contrast, subjects in the lower efficacy condition experienced a dramatic reduction in revitalization during activity, before returning to baseline levels postexercise.

We submit that such findings speak to consequences that derive directly from the intrinsic qualities of the exercise experience. In general, more efficacious individuals display greater coping abilities during challenging tasks (Bandura, 1986) and tend to experience enhanced efficacy as a function of mastering the task at hand (e.g., McAuley, Courneya, & Lettunich, 1991). Moreover, it has been suggested and empirically supported (McAuley & Courneya, 1992) that affective responses experienced during challenging tasks such as graded exercise contribute to such enhancements in efficacy. Although the exact nature of such a relationship remains unclear (i.e., which type of affect contributes to increased efficacy), feelings of revitalization play a key role here, insomuch as lethargy is often symptomatic of depression (Bumam, Wells, Leake, & Landsverk, 1988). Further exploration of the reciprocal nature of the efficacy-revitalization link is warranted.

The results indicating that more efficacious females displayed a linear increase in positive engagement and that the less efficacious subjects demon- strated an inverse pattem across the exercise bout (pre-, during, and postactivity) are consistent with other reports in the literature (e.g., McAuley & Coumeya, 1992). In our view, the Positive Engagement subscale of the EFI captures the affective variation that typically is argued to reside in the positive affect dimension of the positive-negative affective taxonomy (e.g., Watson, Clark, & Tellegen, 1988). However, the advantage of assessing positive affect with the EFI as opposed to instruments such as the Positive and Negative Affect Schedule (Wat- son et al., 1988) lies in its ability to effectively tap those items (happy, enthusiastic, upbeat) that are likely to be influenced by the stimulus qualities of the exercise experience (Gauvin & Rejeski, 1993).

We had expected to see group differences in the other affective responses measured by the EFI (i.e., tranquility and physical exhaustion). However, the pattem of responses was practically identical for both groups in terms of tranquil- ity, with both groups reporting reductions during activity and with postactivity responses returning to baseline values. It might be argued that the social-environ- mental setting of the exercise stimulus plays an important role in how such responses are emitted. That is, the sterile laboratory environment may be less inclined to induce tranquil responses than will a run in a forest, along a river, or with companions. Further research is recommended in which environmental

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conditions are either contrasted or manipulated to test such an assertion. From amore complex perspective such contrasts should also be examined while compar- ing preexercise cognitive sets (e.g., efficacy).

With respectto the lack of differences between efficacy conditions on the physical exhaustion subscale, the degree of exercise intensity must be considered. Subjects exercised for 20 min at 70% of their HRR. Given that subjects in both conditions had comparable levels of aerobic capacity and that the duration and intensity of activity were not maximally taxing, it is perhaps not unexpected that subjects demonstrated similar patterns of physical exhaustion responses. Future empirical efforts might be directed at teasing out the role played-by efficacy in moderating exhaustion in a dose-response fashion (Rejeski, 1994).

In summary, we believe that further evidence has been presented to support the reliability and validity of the EFT. However, it should be remembered that the demonstration of the construct validity of any psychometric measure is an ongoing process and that the structure of the EFI should continue to be tested across the demographic and physical activity spectrum. Whether the dimension of feeling states assessed is sufficient or whether these states underlie a more global set of responses is not clear. It is clear, however, that instruments such as the EFI will provide us with more useful psychometric tools with which to assess the influence of exercise and physical activity on mental health responses.

References

Astrand, P.O., & Rhyming, I. (1954). A nomogram for calculation of aerobic capacity (physical fitness) from pulse rate during submaximal work. Journal of Applied Physiology, 7 , 218.

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice Hall.

Blair, S.N., Kohl, H.W., Paffenberger, R.S., Jr., Clark, D.G., Cooper, K.H., & Gibbons, L.W. (1989). Physical fitness and all-cause mortality: Aprospective study of healthy men and women. Journal of the American Medical Association, 262, 2395-2401.

Borg, G. (1985). An introduction to Borg's RPE-Scale. Ithaca, NY: Mouvement. Bumam, M.A., Wells, K.B., Leake, B., & Landsverk, J. (1988). Development of a brief

screening instrument for detecting depressive disorders. Medical Care, 26, 775- 789.

Cutrona, C.E., & Troutman, B.R. (1986). Social support, infant temperament, and parenting efficacy: A mediational model of post-partum depression. Child Development, 57, 1507-1518.

Gauvin, L., & Rejeski, W.J. (1993). The Exercise-Induced Feeling Inventory: Development and initial validation. Journal of Sport & Exercise Psychology, 15, 403-423.

Karvonnen, M.J. (1957). The effects of training on heart rate: A longitudinal study. Annals of Medical and Experimental Biology, 35, 305.

Landers, D.M. & Petruzzello, S.J. (1994). Physical activity, fitness, and anxiety. In C. Bouchard, R.J. Shephard, & T. Stephens (Eds.), Physical activify,fitness, and health: International proceedings and consensus statement (pp. 868-882). Champaign, IL: Human Kinetics.

McAuley, E. (1991). Efficacy, attributional, and affective responses to exercise participa- tion. Journal of Sport & Exercise Psychology, 13, 382-393.

Self-Efficacy and Feeling States / 333

McAuley, E. (1994). Physical activity and psychosocial outcomes. In C. Bouchard, R.J. Shephard, & T. Stephens (Eds.), Physical activity,fitness, and health: International proceedings and consensus statement (pp. 551-568). Champaign, IL: Human Kinetics.

McAuley, E., & Coumeya, K.S. (1992). Self-efficacy relationships with affective and exertion responses to exercise. Journal of Applied Social Psychology, 22,312-326.

McAuley, E., & Courneya, K.S. (1994). The Subjective Exercise Experiences Scale (SEES): Development and preliminary validation. Journal of Sport & Exercise Psychology, 16, 163-177.

McAuley, E., Coumeya, K.S., & Lettunich, J. (1991). Effects of acute and long-term exercise on self-efficacy responses in sedentary, middle-aged males and females. The Gerontologist, 31, 534-542.

Morgan, W.P. (1985). Affective beneficence of vigorous physical activity. Medicine and Science in Sports and Exercise, 17, 94-100.

Rejeski, W.J., (1994). Dose-response issues from a psychosocial perspective. In C. Bouch- ad, R.J. Shephard, & T. Stephens (Ecls.), Physical activity, fitness, and health: International proceedings and consensus statement (pp. 1040-1055). Champaign, IL: Human Kinetics.

Watson, D., Clark, L.A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063-1070.

Manuscript submitted: January 5, 1994 Revision received: May 13, 1994