1. The Relationship Between Academic Stress and Skeletal Muscle Performance
Voon Chi Chia, Angie L. Wei, Nicole A. Laskosky, Courtney D. Jensen
Department of Health and Exercise Science, University of the Pacific, Stockton, CA
ABSTRACT
Table 1: Demographics
Student athletes are required to perform both in the classroom and on the field; balancing these commitments can be stressful. It is common to question the burden of athletic demands on student scholarship. However, the inverse is seldom asked: how do scholastic stresses affect athletic performance? Many studies show the negative effects of anxiety on performance5; there is also ample research on the effects of pre-game stress on athletic performance.3 However, studies on the physiological effect of scholastic stress on athletic performance is sparse.
PURPOSE: To test the effect of psychological stress on skeletal muscle performance in college students.
METHODS: We enrolled 23 recreationally active students (10 men, 13 women) from a D1 university. Skeletal muscle function was assessed via quadriceps extension and hamstring flexion using a Cybex HUMAC NORM dynamometer. We define stress as the inequality between perceived ability and the amount of demands2; psychological stress was measured with the Cohen Perceived Stress Scale1. Subjects were evaluated at two time points: a high stress period (exams) and a low stress period (no exams). Subjects with history of lower extremity injuries were omitted from participation; nightly sleep, history of exercise, and recent exercise were controlled. Independent variables were stress, sex, age, weight, BMI, academic load, and participation in organized sports (club or intramural). Dependent variables were peak torque (ft/lb) and time to achieve peak torque (sec). Differences in muscle performance between high and low stress periods were assessed with t-tests. Linear regressions analyzed the effect of psychological stress on muscle performance.
RESULTS: Subjects were 20.2 ± 1.1 years old, had peak flexor torque of 87.4 ± 19.7 ft/lb (achieved in 0.58 ± 0.12 sec), and peak extensor torque of ± 37.5 ft/lb (achieved in 0.58 ± 0.15 sec). T-tests found no differences between low and high stress periods in peak torque or time to achieve peak torque (p>0.090). Linear regression found increases in psychological stress correlate with improvements in the overall rate of force development (p=0.004). The effect was most strongly observed in flexors: for each point that stress increased, time to achieve peak torque was 2.4% faster (p=0.002).
CONCLUSION: Although our sample was small, our findings suggest that psychological stress may enhance force development. A possible mechanism is stress-related elevations in epinephrine levels. Although this was not measured, an increase in epinephrine could potentiate calcium release to accelerate contraction. Academic stress likely presents many challenges for student athletes, such as sleep deprivation6, but it might not impair muscular performance.
Characteristics
Female (N = 13)
Male (N = 10)
Age 20
Major 9 8
Course Credits
16.5
15.9
LE Injuries 5 6
BMI
23.0
24.2
Jobs 4
Job (Hours per Week)
2.5
2.7
Sport Participation
10* 1
Intramural Sports 7*
Club Sports 2
[Above] Cybex HUMAC NORM Dynamometer
RESULTS
* = p < LE = Lower Extremity. BMI = Body Mass Index.
Subjects. Among male and female participants, no significant differences were detected in peak torque (p = 0.082) or amount of time to reach peak torque (p = 0.391). All respondents took an average of ± seconds to reach peak torque. Between men and women, no differences were detected in the duration that peak torque was held (p = 0.228) (Table 3).
Relationship between Psychological Stress and Muscle Performance. Regarding change in psychological test values and muscle performance, no significant differences were found between change in peak torque (p = 0.992) or the duration of peak torque was held (p = 0.972). However, the relationship shows a change between overall psychological stress and rate of force production (p = 0.026) using the multiple linear regression.
Regression analysis. The Regression Residual Model (F = 9.392, p = 0.001) explained about 48% of the variance in the time to reach peak torque. According to the model, with each point that the Overall Psych Score increased, peak torque was accomplished about a tenth of a second faster (95% Confidence Interval: to ).
Table 2: Two-Week Period Evaluations
Female
Male
Low Stress
High Stress
Exercise per Week
2.385
2.231
2.400
2.300
Duration (Hours)
2.308
2.615
2.600
2.800
Sleep (Hours)
3.231
3.000
3.077
Table 3: Muscle Function Tests (Mean ± SD)
Female (N = 13)
Male (N = 10)
Sum Peak Torque Flexor and Extensors ± ±
Overall Average Time to Peak Torque
0.599 ± 0.136
0.554 ±
Overall Average CYBEX Duration of Peak Torque ± ±
SUMMARY AND CONCLUSIONS
EXPERIMENTAL DESIGN AND METHODS
While we found that mental stress did not significantly affect peak torque or the duration peak torque was held, we found that stress did have an inverse relationship with the time it took to achieve peak torque. Psychological stress experienced by university students and athletes may not be as detrimental as we initially assumed. Our findings suggest that an increase in stress could potentially accelerate force development. For athletes, an increase in stress may mean an enhancement of performance as the rate of force generation is critical to optimal performance in explosive sport contexts.
Future research with larger samples and diverse populations would be needed to confirm our findings. Additionally, the conditions of stress should be varied and more comprehensive. Our chosen population, the number of enrolled subjects, the conditions of stress, and the duration of our research protocol limit the generalizability of our findings.
The research population consisted of male (n=10) and female (n=13) undergraduate students of various majors and class standings who were currently enrolled full time at a D1 university in northern California.
Our inclusionary criteria were 1) full-time college enrollment, and 2) age between 18 and 22 years. The exclusionary criterion was lower extremity injuries that prohibited muscle testing or extreme psychological distress, which may confound functioning. Ethical concerns were addressed by de-identifying all subjects in the database.
Prior to muscle function testing on the Cybex HUMAC NORM dynamometer, we recorded demographic, behavioral, and anthropometric data: height, weight, BMI, age, sex, major, academic load, frequency and duration of exercise per week, amount of sleep per night, and history of lower extremity injury. Occupations and university extracurricular sport engagement (intramural and club) were also considered in the muscle test. Data collected using the Cybex system included peak torque, time to peak torque, and duration peak torque was held. The subjects performed this protocol at two time points during the semester to compare stress levels. Psychological stress was assessed with the 10-Point Cohen Perceived Stress Scale Questionnaire, which evaluated the degree of stress the individual was currently experiencing and how they were responding to that stress. Subjects answered numerically on a scale of 1-4; answers were summed to obtain a composite score.
Statistics. All tests were performed using SPSS version 22 (IBM SPSS Statistics, IBM Corporation, Chicago, IL, USA). Differences between men and women were measured with chi-square and t-tests. Linear regression analyses tested the effect of psychological stress score on skeletal muscle function. Significance was set at p <
Table 4: Multiple Linear Regression
Model R
R Square 1
0.696a
0.484
Model
Sum of Squares Df
Mean Square F
Sig.
1 Regression Residual Total
0.053
0.056
0.109 2 20 22
0.026
0.003
9.392
0.001b
Model
Unstandardized Coefficients
Standardized Coefficient t
Sig.
95% Confidence Interval for B
Collinearity Statistics B
Std. Error
Beta
Lower Bound
Upper Bound
Tolerance 1
(Constant)
Change in Overall Psych Score
Intramural or Club Sport participation
-0.200
-0.009
0.074
0.015
0.003
0.023
-0.524
3.239
-1.291
-3.242
0.211
0.004
-0.052
-0.014
0.026
0.012
-0.003
0.121
0.986
REFERENCES
1. Cohen, S., Kamarck, T., and Mermelstein, R. (1994) A global measure of perceived stress. Journal of Health and Social Behavior, 24, Einberg, R.S., & Gould, D. (2015) Foundations of sport and exercise psychology (5th Ed.). Champaign, IL: Human Kinetics.
3. Fullerton, C.M. (n.d.) Stress and anxiety in athletics. United States Sports Academy America’s Sports University, The Sport Digest. ISSN:
4. Humac Norm. (n.d.) Retrieved from extremity-systems/humac-norm
5. LeBlanc, V.R. (2009). The effects of acute stress on performance: Implications for health professions education. Academic Medicine, 84(10), S25-S33.
6. Pilcher, J.J., & Huffcutt, A.I. (1996). Effects of sleep deprivation on performance: A meta- analysis. Sleep, 19(4):