2017 Undergraduate Research
The Relationship of Sleep Quality and Sleep Quantity to Athletic Performance
Allison Kosobud
Exercise Science and Sport Study, Integrative Health Sciences, NATS, Psychology
Athletes need more sleep than non-athletes in order to recover after training and achieve top performance, yet often experience low quality sleep. In short-term laboratory studies, athletes that increased their sleep quality and quantity also experienced marked improvements in mood and athletic performance. PURPOSE: To examine how sleep quality, sleep quality, and mood relate to athletic performance over an entire season. METHODS: Twenty-nine healthy Division III female swimmers and track & field athletes (ages 18-22) measured their sleep quality and quantity for two nights prior to each meet using the Sleep Cycle app. Two hours prior to each meet, participants completed the Profile of Mood States (POMS) survey. After each meet, the participants reported their daily sleep quality and sleep quantity values, as well as performance results from their meet. Performance scores were calculated as the percentage of each participant’s ‘personal record’ time/distance in the event. The two-night sleep quality scores and quantity scores were individually averaged. RESULTS: Three Pearson product-moment correlations were performed to examine the relationships of sleep quality, sleep quantity, and mood with performance. The analyses revealed significant positive correlations between sleep quality and performance [r(78) = .226, p < .05] and between mood and performance [r(78) = .252, p < .05]; a non-significant relationship was found between sleep quantity and performance [r(78) = .215, p > .05]. CONCLUSION: Both sleep quality and mood are weakly related to performance, with each of the two variables accounting for less than 5% of all of the variance in performance.
Validity of Fitbit Charge in College Students during Free-Living Conditions
Molly Heller
Exercise Science and Sport Study, Integrative Health Sciences, NATS
Hip-worn Fitbits are a valid measure of step counts and energy expenditure in middle-aged populations, but the validity of the new wrist-worn Fitbit Charge has not been established. PURPOSE: The purpose of the current study was to determine the validity of the Fitbit Charge in estimating step count and caloric expenditure in a college population during free-living conditions. METHODS: The current study used a descriptive and experimental design to determine the concurrent validity of the step counts and caloric expenditures calculated by Fitbit Charge, using the step counts from Yamax SW-701 pedometer and caloric expenditure from Polar Team 2 Heart Rate Monitor, respectively, as the criterion measures. Forty-four healthy college-aged students (9 male, 35 female; 20 ± 0.92 years) wore three devices, the Fitbit Charge, Yamax SW-701 Pedometer, and Polar Team 2 Heart Rate Monitor, for 12 hours (7am-7pm) each during free-living conditions. The data from each device was downloaded onto a notebook computer and analyzed. RESULTS: Step counts from the Fitbit Charge were positively correlated with step counts from the Yamax SW-701 Pedometer, Pearson’s r(39) = .942, p < .001. A paired samples t-test indicated that the Fitbit Charge recorded a significantly greater number of steps (9322 ±3958 steps) than the Yamax SW-701 pedometer (8776 ±3606 steps), t(38) = 2.561, p = .015, d = 0.14. The caloric expenditure from the Fitbit Charge was positively correlated with the caloric expenditure from the Polar Team 2 Heart Rate Monitor, Pearson’s r(29) = .501, p = .006. A paired samples t-test indicated the Fitbit Charge recorded significantly few calories expended (1497 ±334 calories) compared to the Polar Team 2 Heart Rate Monitor (2177 ±782 calories), t(28) = -5.394, p < .001, d = 1.13. CONCLUSION: The validity of the Fitbit Charge in measuring step count or caloric expenditure was not established. The strong positive correlation between step counts reported by the Fitbit Charge and the Yamax SW-701 pedometer, along with the small effect size, indicate the Fitbit Charge may have a small systematic error. The moderate correlation between the caloric expenditure calculated by the Fitbit Charge and the Polar Team 2 Heart Rate Monitor, along with the large effect size, indicate the two methods utilize distinctly different variables in calculating caloric expenditure.
Psychosocial Effects of Studying Abroad in South Africa and Return to the United States
Kevin Curwick
Exercise Science and Sport Study, Integrative Health Sciences, NATS, Psychology
Studying abroad is a challenging time for an individual’s mental health as there are additional factors that influence students’ health decisions. Strain felt by students abroad has been explored in a variety of studies, but without the context of returning to their home country. PURPOSE: The aim of the study was to examine the change in perceived social support, homesickness, and alcohol consumption while abroad and after returning to the participants’ home university. Additionally, the study examined the relationship between perceived social support and homesickness while abroad and after returning to the participants’ home university. METHODS: Eight participants (aged 20-21 years) completed the Homesickness Questionnaire (HQ) and the Multidimensional Scale of Perceived Social Support (MSPSS) at the beginning and end of the semester abroad in South Africa and the semester after returning home. The Sojourner Adjustment Measure (SAM) was only completed at the beginning and end of the semester abroad, while the Reentry Shock Scale was only completed at the beginning and end of the semester upon returning to the participants’ home university. RESULTS: A repeated measures ANOVA yielded no significant effect of time on HQ scores, F(3,21) = 1.947, p = .153, MSPSS scores F(3,21) = 1.545, p = .232, or alcohol consumption F(3,21) = .289, p = .833. HQ scores were significantly correlated with MSPSS scores while abroad (r(8) = -.732, p = .039), but not while at home (r(8) = -.418, p = .303). There were no significant changes in participants’ SAM scores from the beginning of their semester abroad (M = 109.63, SD = 10.86) to the end of their semester abroad (M = 110.75, SD = 12.34), t(7) = .759, p = .472. Participants experienced no differences in reentry shock between the beginning of their semester at home (M = 69.38, SD = 10.65) and the end of their semester at home (M = 71.50, SD = 11.15), t(7) = .952, p = .472. CONCLUSION: Participants appear to cope well with the strain of studying abroad with no significant impact on measured health behaviors. The strong inverse relationship between perceived social support and homesickness while abroad suggests that improved perceptions of social support and adjustment to host culture may contribute to reductions in homesickness while abroad.
The Effects of an Extended Rest Period After a Warm-Up in Cold Conditions
In outdoor sports such as ultimate frisbee, non-starting athletes commonly warm up with the team and then rest on the bench in cold weather until entrance into the game. PURPOSE: The purpose of the current study was to examine the effect of a warm up followed by prolonged rest period in a cold environment on power performance. METHODS: Five female ultimate frisbee players (age = 20.6 ±0.89 years; height = 163.07 ±3.31 cm; weight = 70.28 ±10.01 kg; % body fat = 23.73 ±4.08%) completed 4 separate trials, with each trial taking place on a separate day over a 3-week period. Each trial consisted of a warm up (5 minutes moderate cycling, 8 minutes lower body dynamic stretching), a rest interval (0, 10, or 20 minutes), a re-warm up (1 minute jogging in place, 1 minute lower body dynamic stretching), and physiological testing immediately following the rewarm up. The physiological testing consisted of 3 maximum vertical jump (VJ) trials with the best score recorded, followed by a 30-second anaerobic-cycling Wingate test. Peak power (PP) and mean power (MP) were calculated from the Wingate test. Trial 1 and trial 2 served as controls in a thermoneutral environment (24°C) and cold environment (0°C), respectively, with a rest interval of 0 minutes in both trials. Trial 3 and 4 served as the experimental trials in the cold environment (0°C) with a 10-minute and 20-minute rest interval, respectively. Trials occurred in the same order for each of the 5 participants. RESULTS: A one way repeated measures ANOVA showed a significant difference in the mean VJ height between trials, F(3, 12) = 5.332, p = .014, ηp2= .571. Least Significant Difference post hoc t-tests revealed a significant difference in mean VJ height between trial 1 (thermoneutral condition with no rest period; 39.8 ±7.4 cm) and trial 4 (the cold condition with a 20-minute rest period; 35.8 ±6.9 cm). A repeated measures ANOVA with a Greenhouse-Geisser correction did not show a significant difference in mean PP between trials or mean MP between trials. CONCLUSION: The current study found a significant decline in power (VJ) over trials, while anaerobic capacity (PP and MP) was not affected by the prolonged rest period in a cold environment.
The Effects of Hatha Yoga on Vital Capacity of College-Aged Students
Hatha yoga has been purported to be beneficial in increasing respiratory efficiency and enhancing pulmonary function after several months of committed practice. There is currently limited research addressing the short-term effects of one session of Hatha yoga on pulmonary function. PURPOSE: The purpose of the current study was to examine the acute effects of Hatha yoga on vital capacity (VC). METHODS: Twenty healthy participants (Male: n=1; Female: n=19; Age: 20.1 ± 1.1 years; Height 166.6 ± 6.9 cm) who were not a member of a club or varsity collegiate sport team were randomly assigned to either the control (n=10) or experimental group (n=10). Pre-test physical activity was not controlled. A baseline VC test was performed for each participant using a spirometer. The experimental group then performed one hour of Hatha yoga, while the control group remained sedentary. After the yoga session, VC was measured again using the same protocol. VC measures were normalized as a percentage of the participant’s estimated total lung capacity (TLC). The change in VC was calculated by subtracting normalized pre-test VC from normalized post-test VC. RESULTS: An independent samples t-test revealed a non-significant difference in normalized baseline VC values between the control and experimental groups. An independent-samples t-test indicated a significant difference in the change in VC from pre-test to post-test between the control group (-0.034 ± 0.042% of TLC) and the experimental group (0.001 ± 0.029% of TLC), t(18) = 2.164, p = .044, d = 0.97. CONSLUSION: One hour of sedentary behavior resulted in a large decrease in VC, while performing one hour of Hatha yoga helped maintain VC. Funding: CSB/SJU Undergraduate Research Production Grant
Exercise and Intersectionality
Women exercise less than men beginning in adolescence. Furthermore, black women have a higher rate of physical inactivity than white women. Therefore, for women of color, race and gender combine to compound the barriers to physical activity, making it difficult to exercise. PURPOSE: The current study seeks to examine barriers to physical activity experienced by white and non-white college-aged women. METHODS: Two-hundred-thirty-one college-aged women participated in a survey that included the Exercise Benefits and Barriers Scale (EBBS), questions pertaining to exercise identity, and demographic questions. Eight of the participants also participated in focus groups that examined exercise barriers associate with race (white women: n = 6, non-white women: n = 2). RESULTS: A series of Mann-Whitney U tests were conducted to compare the ranked scores of white women to non-white women. The statistical analysis showed that the two groups were significantly different in reported exercise frequency, with the white group (Mdn = 4 to 7 times per week) exercising more often than the non-white group, (Mdn = 1 to 3 times per week), U = 2838, p =.001. The white group (Mdn EBBS rank = 136.5) also had a significantly more positive perception of exercise than the non-white group (Mdn EBBS rank = 125.00), U = 2344.5, p < .001. The white group (Mdn = 4) had a significantly stronger self-perception as an exercisers than the non-white group (Mdn = 3), U = 2196.5, p < .001. The white group (Mdn = 4) significantly believed their health to be a priority more than the non-white group (Mdn = 4), U = 2387, p < .001. The white group (Mdn = 4) also significantly perceived themselves to exercise with the same race more than the non-white group (Mdn = 4), U = 2681.5, p < .001. CONCLUSION: White women perceive exercise more positively than non-white women, which may contribute to the disparity in exercise frequency.
The Effects of Studying Abroad on College Students’ Exercise and Nutritional Habits.
Studying abroad challenges students’ overall health as cultural factors influence their decisions. Students’ activity and nutritional habits, abroad as well as on-campus, are largely dependent on socioeconomic and cultural norms. PURPOSE: The purpose of this study was to examine physical activity behaviors and dietary consumption of students while studying abroad in South Africa and on-campus. METHODS: Subjects included 16 physically healthy students (20-22 years). Data were collected during four separate, weeklong blocks: beginning and end of the semester abroad as well as the semester on-campus. A modified Alternative Healthy Eating Index—2010 (AHEI—2010) was used to track nutritional habits. Anthropometric measurements (body fat %) were taken using Lange skinfold calipers following ACSM’s seven-site skinfold method. Activity levels were measured via step count from Fitbit Charge monitors worn during each testing block. RESULTS: A 2x2 repeated measures ANOVA was conducted that examined the effect of location (abroad, on-campus) and time (beginning of semester, end of semester) on body composition. The interaction effect between location and time was not significant, F(1, 15) = .012, p = .913. The main effect for location was significant, F(1, 15) = 6.127, p = .026, ηp2 = .290, while the main effect for time was not significant , F(1, 15) = .629, p = .440. A paired-samples t-test revealed no significant difference in physical activity abroad (10,271 ±2607 steps) in comparison to physical activity at home (11,622 ±5227 steps), t(16) = 1.317, p = .205. Paired-samples t-tests indicated increased consumption of sugar, t(8) = 2.501, p = .041, increased consumption of refined grains, t(8) = -2.898, p = .023, and decreased consumption of fruit, t(8) = 2.663, p = .032, while abroad in comparison to on-campus. CONCLUSION: Studying abroad did not affect students’ overall physical activity compared to studying on their home campus, but nutrition habits changed, likely due to food access and cultural norms. The change in body composition was similar during the semester abroad and at home. Students had a greater percentage body fat while abroad compared to at home, but the difference is likely due to extraneous variables. Regardless, students should be conscientious of their health while studying abroad and at home.