The Correlation Between Physical Activity and Grade Point Average for Health Science Graduate Students Eugenia C. Gonzalez, PhD, OTR; Erika C. Hernandez, OTR/L; Ambrosia K. Coltrane, OTR/L; and Jayme M. Mancera, OTR/L key words: physical activity, grade point average, allied health graduate students ABSTRACT Researchers have reported positive associations between physical activity and academic achievement. However, a common belief is that improving academic performance comes at the cost of reducing time for and resources spent on extracurricular activities that encourage physical activity. The purpose of this study was to examine the relationship between self-reported physical activity and grade point average (GPA) for health science graduate students. Graduate students in health science programs completed the International Physical Activity Questionnaire and reported their academic progress. Most participants (76%) reported moderate to vigorous physical activity levels that met or exceeded the recommended levels for adults. However, there was no significant correlation between GPA and level of physical activity. Negative findings for this study may be associated with the limited range of GPA scores for graduate students. Future studies need to consider more sensitive measures of cognitive function, as well as the impact of physical activity on occupational balance and health for graduate students in the health fields. [OTJR: Occupation, Participation and Health. 2014; 34(3):160-167.]
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ne of the national objectives set by Healthy People 2020 is to increase the amount of moderate to vigorous physical activity people engage in daily to improve their health, fitness, and quality of life (U.S. Department of Health and Human Services [HHS], 2011). However, more than 80% of adults and youth do not meet the required standards for moderate and vigorous physical activity associated with improved health (HHS, 1996). For adults, regular physical activity is known to lower the risk of coronary heart disease, type 2 diabetes, stroke, and some types of cancer. For children
and adolescents, regular physical activity has been shown to improve bone health, improve cardiorespiratory and muscular fitness, and decrease levels of body fat. Additionally, for adults and adolescents, regular physical activity is associated with reduced symptoms of depression (HHS, 1996). Therefore, the impact of regular physical activity at a moderate to vigorous level has been clearly linked to improved health and well-being (HHS, 1996; McMurrer, 2007). Physical activity has also been linked to academic achievement in children (Ploughman, 2008; Trost & van der Mars, 2009/2010). However, since
Dr. Gonzalez is Assistant Professor, Occupational Therapy Program, The University of Texas at El Paso, El Paso, Texas; Ms. Hernandez is Occupational Therapist, Aprendamos Intervention Team, Las Cruces, New Mexico; Ms. Coltrane is Occupational Therapist, Texas Children’s Hospital, Houston, Texas; and Ms. Mancera is Pediatric Occupational Therapist, Easter Seals of West Georgia, Columbus, Georgia. Submitted: August 2, 2013; Accepted: June 30, 2014; Posted online: July 25, 2014 The authors have no financial or proprietary interest in the materials presented herein. This study was conducted with the approval of the Institutional Review Board at the University of Texas at El Paso. Address correspondence to Eugenia C. Gonzalez, PhD, OTR, 6611 Boeing, El Paso, TX 79925; e-mail: [email protected]. doi:10.3928/15394492-20140714-01
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the No Child Left Behind Act was enacted in 2002, more than 62% of elementary schools and 20% of middle schools increased the instructional time allotted to reading and math (Trost, 2009; Trost, & van der Mars, 2009/2010). Increased instruction time in math and reading was matched with reductions in time allocated to the liberal arts and physical education (Trost & van der Mars, 2009/2010). Lee, Burgeson, Fulton, and Spain (2007) reported that based on a nationwide survey of schools, only 3.8% of elementary schools, 7.9% of middle schools, and 2.1% of high schools offered daily physical education (PE) for the entire school year. The assumption being that by reducing time spent in extracurricular activities and increasing time spent on academics, students would demonstrate an improvement in academic performance. However, there is emerging evidence that reducing physical activity may be counterproductive to improving academic performance. In a longitudinal study done in Quebec, Canada, elementary school students were assigned to different levels of PE per week (Shephard, 1996, 1997; Shephard & Trudeau, 2008; Trudeau & Shephard, 2008). Students were assigned to participate in either 40 minutes of physical activity per week (control group) or 5 hours of physical activity per week (experimental group). Children in the experimental group scored higher than children in the control group on provincial examinations (i.e., annual academic examinations given to students in Canada). However, the experimental group scored higher than the control group only on the math portion of the examination, not the English portion. These results were interesting given that students in the experimental group were pulled out of their math classes to exercise but not pulled out of their English classes (Shephard et al., 1984). From a review of recent literature, Trost and van der Mars (2009/2010) reported that research conducted to investigate the effect of physical activity on academic performance, cognition, IQ, and standardized tests on elementary students supports the hypothesis that physical activity improves academic performance. Although not all studies identified in the literature have resulted in a positive effect of physical activity on academic performance, none of the studies reviewed reported a negative effect of physical activity on academic performance (Ahamed et al., 2007; Sallis et al., 1999). Evidence for the positive association between physical activity and academic performance is also present for students in middle and high school. Nelson and Gordon-Larsen (2006) had students in grades 7 to 12 participate in moderate to vigorous physical
activity five or more times weekly. Although they were investigating the effects of increased physical activity on risky behaviors and self-esteem, they also examined the effect of physical activity on academic achievement. Students in the group that participated in moderate to vigorous physical activity were more likely to earn an A grade in math or science than students who were less active. The Nelson and GordonLarsen (2006) study, therefore, provides evidence of the positive effects of physical activity on the academic performance of middle and high school students. However, no other studies related to physical activity and academic performance for this age group were identified by these authors. Studies that have used cognitive function as an outcome measure have also provided support for the positive association between physical activity and academic performance. Davis et al. (2011) used cognitive and academic achievement measures to study the effect of different doses of physical activity, specifically aerobic exercise, for children who were overweight and sedentary. They concluded that there was an effect of dose or level of physical activity such that children who participated in the highest dose of physical activity demonstrated the greatest improvement in executive function. Additionally, Davis et al. (2011) conducted functional magnetic resonance imaging (MRI) measures of brain activity during executive function tasks for a subset of their participants. They reported that the MRI data provided evidence that physical activity increased the prefrontal cortex activity bilaterally and decreased posterior parietal cortex activity; the combined action contributed to improved ability to plan ahead, inhibit inappropriate behaviors, and delay gratification. Therefore, they concluded that physical activity has an effect on academic performance by way of these brain systems that are directly related to cognition and behavior. The findings reported by Davis et al. (2011) are consistent with cognitive changes reported for older adults. From a meta-analysis of studies with older adults, Colcombe and Kramer (2003) concluded that aerobic fitness training also increases executive function in older adults (55 and older). This was especially true for executive control processes such as planning, inhibition, and scheduling of mental procedures (e.g., responding to a central or relevant cue while suppressing a response to an irrelevant cue presented simultaneously). More recent studies of healthy older adults have also provided support for the positive association between moderate to vigorous physical activity and improved cognitive function (Lautenschlager et al., 2008; Masley, Roetzheim, & Gualtieri, 2009).
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Additionally, from a review of the literature related to physical activity and cognitive function of older adults, Weinstein and Erickson (2011) concluded that physical activity enhances brain function as well as protects the brain against age-related decline associated with physiological changes present with normal aging. Studies in their review used structural and functional MRIs of human brains to examine changes related to physical activity. Their review included epidemiological, cross-sectional, and experimental studies. Overall, fitness levels have been linked to improved cognitive function and decreased risk for developing age-related cognitive problems (Weinstein & Erickson, 2011). From a review of studies on college students’ physical activity, Keating, Guan, Piñero, and Bridges (2005) reported that studies have been primarily focused on description of physical activity patterns and determinants of physical activity participation for this population. The second most common area of research with college students has focused on intervention studies to increase physical activity among college students. Research related to the relationship between physical activity and academic achievement or cognitive function of college students appears to be lacking. An exception is a survey study of undergraduate college students reported by Flynn, Coe, and Ode (2010). They reported that students who participated in vigorous physical activity 7 days per week had grade point averages (GPAs) four-tenths of a point higher (on a scale of 0 to 4) than those who did not participate in vigorous physical activity (Flynn et al., 2010). Although research with college students is limited, results of Flynn et al.’s (2010) study were consistent with results reported for younger students. Even though the role of student extends from childhood to adulthood, the demands and challenges of this occupation vary at different stages of education. Graduate school introduces a rigor and demand for excellence that is typically not present at the undergraduate level. Given the high academic standards and the importance of accurately learning the high volume of information needed for future application with vulnerable populations, students may find themselves placing greater emphasis on studying at the cost of balancing activities that include health behaviors such as exercise/fitness. The demands of occupational therapy programs and other professional programs may make it more difficult for students to maintain a healthy balance of occupations, roles, and leisure activities. Anecdotally, graduate students often report they were able to maintain a comfortable balance of roles, occupa-
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tions, and activities as undergraduates that they are not able to achieve as graduate students. Therefore, the purpose of this study was to examine the relationship between physical activity and GPA for graduate students enrolled in allied health programs at one college of health sciences in a university along the Texas-Mexico border. We hypothesized that the positive correlation between GPA and moderate to vigorous physical activity reported for younger students would also be present for graduate students enrolled in health sciences programs. The questions to be answered were: 1. What percentage of allied health graduate students report they participate in vigorous, moderate, or no physical activity? 2. Does physical activity level have a significant positive correlation with GPA for graduate students? 3. Are there differences in level of physical activity reported based on participants’ gender, ethnicity, or type of program in which the student is enrolled?
Method Research Design This was a retrospective study of graduate students’ self-reported physical activity and one marker of academic performance, GPA. Surveys were distributed to students in the participating health science programs during the same week before the end of the spring semester. Permission was attained from professors in each program to distribute the surveys at the beginning or end of a scheduled class. This strategy ensured all students in a cohort were contacted. Students were asked to sign a consent form that explained the study and confirmed that they could refuse to participate without penalty. Students then had the option to complete the International Physical Activity Questionnaire (IPAQ) short form and a demographic questionnaire. Surveys were labeled with the study number and separated from signed consent forms to ensure students’ information remained confidential. This study was conducted with the approval of the University Institutional Review Board. Participants Graduate students enrolled in health science programs at the University were asked to participate in the study. Participating programs included occupational therapy, physical therapy, speech language pathology, rehabilitation counseling, and pharmacy. Participation was limited to these programs because they share a common class-
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room building to hold environmental influences on physical activity constant. The University has a primarily Hispanic student body that reflects the population of the region. Measures International Physical Activity Questionnaire (Short Form). The IPAQ short form is a 7-item self-report measure of physical activity (IPAQ, 2005). The tool was designed for population surveillance of physical activity for people ages 15 to 69. It can be selfadministered or completed in a telephone/interview format. The IPAQ assesses physical activity undertaken in four domains: leisure time physical activity, domestic and gardening activities, workrelated physical activity, and transport-related physical activity. Participants are asked about walking, moderate-intensity activities, and vigorous-intensity activities undertaken within the four domains outlined above. The IPAQ short form can typically be completed in 10 minutes. The IPAQ short form has been reported to be a good measure of vigorous activity with moderate correlations to maximal oxygen uptake (VO2max), r = 0.41, p ≤ 0.01 (Kurtze, Rangul, & Hustvedt, 2008). The selected metabolic equivalent of task (MET) values used in the classification algorithm were derived from an IPAQ reliability study (Craig et al., 2003) and based on the Ainsworth et al. (2000) compendium. A MET is the ratio of work metabolic rate to a standard resting metabolic rate (Ainsworth et al., 2000). From international studies of the reliability and validity of the IPAQ, test-retest reliability for the short form has been reported as acceptable, with correlation coefficients ranging from 0.88 to 0.32 (Craig et al., 2003). Concurrent validity between the short and long forms was reported as good (pooled p = 0.67, 95% confidence interval [CI] 0.64, 0.70). Criterion validity of the short form was established by comparing selfreported activity against actual activity measured using Computer Science and Application’s Inc. accelerometers and was determined to be fair (p = 0.30, 95% CI 0.23, 0.36) (Craig et al., 2003). Both categorical and continuous scores can be derived from the IPAQ short form (IPAQ, 2005). The scoring algorithm provided for the IPAQ short form was used to classify participants’ reported physical activity as low, moderate, or high intensity (categorical scores). The MET values and formula for computation of MET-minutes/week provided in the IPAQ guidelines were used to calculate the total physical activity MET-minutes/week for continuous scores. (Data processing and scoring criteria are available online at http://www.ipaq.ki.se/scoring.pdf).
Demographic Questionnaire. This is a 6-item questionnaire developed for this study to gather demographic information and self-reported academic progress. Students were asked to report their age, gender, ethnicity, college of enrollment, and projected graduation date. They were also asked to report their current GPA to the nearest hundredth decimal point (i.e., 0.00). Statistical Analysis Data were analyzed using SPSS version 20. Guidelines proposed by the IPAQ Research Committee were used for data cleaning and processing the current data set (IPAQ, 2005) as follows: 1. All duration responses were recorded as minutes per day. 2. Cases with missing data or reported as “I don’t know or not sure” were removed from analysis. 3. Cases in which sum of any time variable was greater than 960 minutes (16 hours) were also excluded (assume 8 hours/day is spent sleeping). 4. Responses of less than 10 minutes were recoded as zero as recommended (because bouts of at least 10 minutes are required to achieve health benefits). 5. The times reported for walking, moderate, and vigorous activity participation that were greater than 180 minutes were truncated to be equal to 180 minutes. This was recommended to normalize the distribution of activity levels, which tend to be skewed in national or large population data sets (IPAQ, 2005).
Results There were 102 surveys distributed, and 100 were returned for analysis (98% return rate). The sample was primarily female (73%) and Hispanic (62%). Most students (42%) were in the third semester of their program. Characteristics of participants by program of study are reported in Table 1. Only surveys with complete data were entered into all analyses reported. GPA was the most common omission (six women and two men). Items left blank on the IPAQ were treated as missing data rather than coded as a zero response. Therefore, the smallest number of surveys available for statistical analyses was 81 (79%). GPAs ranged from 2.50 to 4.00 with a mean of 3.62 (SD = 0.29). Only two students reported a GPA lower than the 3.00 expected in graduate school. It is likely that these students were in their first semester of their program and enrolled on a probationary status and were therefore dropped from further analyses. An analysis of variance (ANOVA) for differences in mean GPAs based on the student’s program of study was
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Table 1 Characteristics of Graduate Students by Program of Study Gender Program of Study (n)
Ethnicity
Male
Female
Hispanic
Whitea
Blacka
Asian/Other
OT (19)
4 (21%)
15 (79%)
10 (53%)
5 (26%)
0 (0%)
4 (21%)
PT (27)
11 (41%)
16 (59%)
15 (56%)
9 (33%)
1 (4%)
2 (7%)
SLP (33)
5 (15%)
28 (85%)
21 (64%)
6 (18%)
1 (3%)
5 (15%)
Rehab. counseling (11)
3 (27%)
8 (73%)
10 (91%)
1 (9%)
0 (0%)
0 (0%)
Pharmacy (10)
4 (40%)
6 (60%)
6 (60%)
1 (10%)
1 (10%)
2 (20%)
Total sample (100)
27 (27%)
73 (73%)
62 (62%)
22 (22%)
3 (3%)
13 (13%)
Note. n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling. a Not of Hispanic origin.
not significant, F (4, 87) = 0.519, p = 0.722. Therefore, all students’ GPAs and self-reported physical activity levels were analyzed as an entire group rather than by program of study. GPA for the sample (N = 92) with the outliers removed was 3.64 (SD = 0.25). Overall, graduate students in this study reported physical activity at each level of intensity: low, moderate, and high. However, there were differences in the pattern of physical activity participation based on the program of study. For example, rehabilitation counseling had almost all students reporting vigorous-intensity physical activity and none reporting low-intensity physical activity. A nonparametric test for differences of frequencies within each level for the total sample was not significant. In other words, the difference in number of students participating at each level of intensity was not statistically significant (p = 0.067). The primary hypothesis was that there would be a positive relationship between physical activity and GPA for graduate students in this study. However, there was no correlation between physical activity and GPA when examined as three levels of physical activity (i.e., low, moderate, high), Spearman’s rho = –0.13, p = 0.128. Reported physical activity levels were also analyzed as continuous scores (IPAQ, 2005). The correlation between IPAQ continuous scores and GPA was also not significant at the 0.05 level (Pearson r = –0.12, p = 0.152). The two IPAQ score formats (categorical and continuous) were used in the analysis (ANOVA) to determine whether reported physical activity levels differed by gender, ethnicity, or program of study for this sample. No statistically significant difference was found in either the categorical or continuous scores based on gender: categorical score,
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F (1, 98) = 1.896, p = 0.172; continuous score, F (1, 98) = 1.391, p = 0.241. There was also no statistically significant difference in either the categorical or continuous scores based on participants’ ethnicity: categorical score, F (4, 94) = 0.636, p = 0.638; continuous score, F (4, 94) = 0.440, p = 0.779. However, a statistically significant difference was found in the categorical and continuous scores based on participants’ program of study: categorical score, F (4, 95) = 3.815, p = 0.006; continuous score, F (4, 95) = 5.003, p = 0.001. Continuous and categorical scores were significantly different between students in the rehabilitation counseling program and students in the other programs. Table 2 indicates the reported level of physical activity (categorical score) participation by program, and Table 3 shows total physical activity MET-minutes/week (continuous score) by program.
Discussion The current study was prompted by studies of physical activity and its relationship with academic performance because graduate students are concerned with their academic success. A common belief is that improving academic performance comes at the cost of reducing time for and resources spent on extracurricular activities that encourage physical activity. Therefore, future studies need to address other benefits of physical activity for students in professional programs. For example, from a study of medical students in different stages of their medical training, Jamali et al. (2013) reported that participation in daily physical activity was significantly associated with higher physical component scores derived from the 36-
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Table 2 Level of Physical Activity by Program and for Total Sample Program of Study (n) OT (19)
Low
Moderate
High
Minimum
Maximum
2 (11%)
8 (42%)
9 (47%)
1
3
PT (27)
7 (26%)
9 (33%)
11 (41%)
1
3
SLP (33)
12 (37%)
11 (33%)
10 (30%)
1
3
Rehab. counseling (11)
0 (0%)
1 (9%)
10 (91%)
2
3
Pharmacy (10)
3 (30%)
4 (40%)
3 (30%)
1
3
Total sample (100)
24 (24%)
33 (33%)
43 (43%)
1
3
Note. n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling.
Table 3 Mean Total Physical Activity MET-Minutes/Week by Program Program of Study (n)
Mean (SD)
Minimum
Maximum
OT (19)
3606.42 (2342.03)
0
8478
PT (27)
2296.43 (1841.05)
0
5958
SLP (33)
2470.27 (2587.25)
0
8892
Rehab. counseling (11)
5919.27 (2609.28)
1485
10158
Pharmacy (10)
3115.05 (3501.19)
0
10638
Total sample (100)
3083.07 (2663.39)
0
10638
Note. MET = Metabolic Equivalent of Task values; n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling.
item Short Form Health Survey. Additionally, scores on all eight of the quality of life domains they measured declined significantly as the stage of the medical student’s education became more difficult (Jamali et al., 2013). The contribution of physical activity to quality of life for graduate college students may be more closely related to achieving occupational balance. For example, Wilson and Wilcock (2005, p. 320) asked beginning-level occupational therapy students the question: “What prevents you from reaching occupational balance?” The primary analysis resulted in three themes—people, time, and money factors as main impediments. Further analysis of the “people” factor, not surprisingly, included factors such as value systems, priorities, motivation, and willpower, as well as skills, knowledge, and level of enjoyment. It was also evident from their analysis of students’ responses that fitness, diet, and health are important factors to consider in attaining occupational balance (Wilson & Wilcock, 2005).
When discussing occupational balance, it is often found that engaging in meaningful occupations brings forth greater quality of life. A vision of occupational therapy is to enhance the well-being of all populations and is not limited to people with disabilities (Wilcock, 2007). Therefore, future studies are needed to explore the factors that impede or facilitate participation for students in the health fields in the level of physical activity that provides the health and academic benefits reported in the literature. From a review of research related to the physical activity of college students, Keating et al. (2005) concluded that changing the sedentary patterns of college students will require collaboration between experts in physical education, exercise physiology, and health. Occupational therapy can provide invaluable insight for future intervention studies related to occupational balance and quality of life. As a former patient of one of the authors once stated, “You have to take care of yourself to be healthy enough to take care of others.”
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Limitations Null findings from the current study may have been related to the lack of sensitivity of the measure used to mark academic performance, GPA. Although a positive association between moderate to vigorous physical activity and GPA has been reported for school-age children and undergraduate students, the range of scores for that population is greater than for graduate students. Undergraduate college students’ grades can range from 0.0 to 4.0. However, at the graduate level, students’ GPA cannot drop below 3.0. This restricted the range in variability of the academic measure used for the current study. Although studies of the relationship between physical activity and academic performance of graduate students were not identified, there have been studies reporting a positive association between brain function and physical activity for older adults. However, these studies have used more precise measures of brain structures and brain function rather than GPA. For example, Weinstein and Erickson (2011) reviewed studies that used structural and functional MRIs of adults’ brains to measure changes associated with participants’ fitness levels. Likewise, Stroth, Hille, Spitzer, and Reinhardt (2009) reported that exercise seems to decrease tissue loss in brain areas relevant to executive control. They recorded increased levels of brain-derived neurotropic factor (BDNF) in adult animal brains after exercise. BDNF is known to be active in the brain areas needed for learning, memory, and higher thinking (i.e., hippocampus, cortex, basal forebrain). Specifically, they reported that changes in BDNF levels were associated with more efficient, plastic, and adaptive cognitive function that is demonstrated as improved learning and performance in adult animals. Although Stroth et al. (2009) reported age-related changes in animal models, their findings have implications for human beings as well. Another limitation of the current study is that admission into the programs included in the study are highly competitive. Therefore, students admitted into those programs have developed skills and strategies that may sufficiently moderate academic performance (as measured by GPA) to mask the effects of nonparticipation in regular physical activity. This competitive quality may also be what influences graduate students’ choice to dedicate a greater amount of time to studying instead of maintaining a healthful balance of activities. The five programs included in the study share an emphasis on patient care. However, there are differ-
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ences in the way the different programs are structured, making it possible that these differences are enough to influence students’ choices to participate in physical activity or not. For example, only the occupational therapy and physical therapy students complete four of their science courses together. These two programs and the speech language pathology program progress students in a lock-step manner so that students in these three programs complete their program with the same cohort. Therefore, students in these three programs do not have choices about the sequence or timing of classes they complete. This was also true for the pharmacy students, with the added requirement of completing their coursework at two different campuses in the state. Students in the rehabilitation counseling program were the only ones not in a lock-step program. This offered them flexibility in the type and amount of classes they completed each semester. This difference may have contributed to the fact that rehabilitation counseling students reported higher levels of physical activity. We chose not to analyze data for each program separately. This was done to reduce the threat of not having sufficient power to detect a difference if in fact one was present in the population. All the professional programs at this college of health sciences have low student-to-faculty ratios. Therefore, it was not possible to recruit more students. Increasing the number of participants from each department in the analysis would require data collection over several years, which would introduce additional threats to validity. Changing to more sensitive measures of academic achievement/performance, as indicated above, would be a preferred solution to this limitation.
Conclusions These data did not support the hypothesis that level of physical activity is associated with GPA for graduate students enrolled in allied health programs. Previous studies have confirmed a positive association between academic achievement and level of physical activity for younger students. There was a trend in the expected direction in that the one program whose students all reported moderate to vigorous physical activity levels was also the only program whose students reported 4.0 GPAs. However, measuring the effects of physical activity on cognitive function of graduate students may require a multidimensional approach that accounts for the interplay of the person’s characteristics and skills, the environmental demands, and their level of occupational performance.
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References Ahamed, Y., Macdonald, H., Reed, K., Naylor, P.J., Liu-Ambrose, T., & McKay, H. (2007). School-based physical activity does not compromise children’s academic performance. Medicine and Science in Sports and Exercise, 39, 371-376. Ainsworth, B., Haskell, W., Whitt, M., Irwin, M., Swartz, A., Strath, S.,...Leon, A. (2000). Compendium of physical activities: An update of activity codes and MET intensities. Medicine and Science in Sports and Exercise, 32(9 Suppl.), S498-S504. Colcombe, S., & Kramer, A.F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science, 14, 125-130. Craig, C.L., Marshall, A.L., Sjostrom, M., Bauman, A.E., Booth, M.L., Ainsworth, B.E.,...Oja, P. (2003). International Physical Activity Questionnaire: 12-country reliability and validity. Medicine and Science in Sports & Exercise, 35, 1381-1396. Davis, C.L., Tomporowski, P.D., McDowell, J.E., Austin, B.P., Miller, P.H., Yanasak, N.E.,...Naglieri, J.A. (2011). Exercise improves executive function and achievement and alters brain activation in overweight children: A randomized, controlled trial. Health Psychology, 30, 91-98. doi:10.1037/a0021766 Flynn, J.I., Coe, D.P., & Ode, J.J. (2010, June). The association between vigorous physical activity & grade point average in college students. Poster presented at the meeting of the American College of Sports Medicine, Baltimore. International Physical Activity Questionnaire. (2005). Guidelines for data processing and analysis of the International Physical Activity Questionnaire—Short and long forms. Retrieved from http:// www.ipaq.ki.se/scoring.htm Jamali, A., Tofangchiha, S., Jamali, R., Nedjat, S., Jan, D., Narimani, A., & Montazeri, A. (2013). Medical students’ health-related quality of life: Roles of social and behavioural factors. Medical Education, 47, 1001-1012. doi:10.1111/medu.12247 Keating, X., Guan, J., Piñero, J., & Bridges, D. (2005). A meta-analysis of college students’ physical activity behaviors. Journal of American College Health, 54, 116-125. Kurtze, N., Rangul, V., & Hustvedt, B.E. (2008). Reliability and validity of the International Physical Activity Questionnaire in the Nord-Trondelag health study (HUNT) population of men. BMC Medical Research Methodology, 8, 63. Retrieved from http:// www.biomedcentral.com/1471-2288/8/63. doi:10.1186/14712288-8-63 Lautenschlager, N.T., Cox, K.L., Flicker, L., Foster, J.K., van Bockxmeer, F.M., Xiao, J.,...Ameida, O.P. (2008). Effect of physical activity on cognitive function in older adults at risk for Alzheimer disease: A randomized trial. Journal of the American Medical Association, 300, 1027-1037. doi:10.1001/jama.300.9.1027 Lee, S.M., Burgeson, C.R., Fulton J.E., & Spain, C.G. (2007). Physical education and physical activity: Results from the School Health Policies and Programs study 2006. The Journal of School Health, 77, 435-463. doi:10.1111/j.1746-1561.2007.00229.x Masley, S., Roetzheim, R., & Gualtieri, T. (2009). Aerobic exercise enhances cognitive flexibility. Journal of Clinical Psychology in Medical Settings, 16, 186-193. doi:10.1007/s10880-009-9159-6 McMurrer, J. (2007). Choices, changes, and challenges curriculum and instruction in the NCLB era. Retrieved from the Center on
Education Policy website: http://www.cep-dc.org/displayDocument.cfm?DocumentID=312 Nelson, M.C., & Gordon-Larsen, P. (2006). Physical activity and sedentary behavior patterns are associated with selected adolescent health risk behaviors. Pediatrics, 117, 1281-1290. doi:10.1542/ peds.2005-1692 Ploughman, M. (2008). Exercise is brain food: The effects of physical activity on cognitive function. Developmental Neurorehabilitation, 11, 236-240. doi:10.1080/17518420801997007 Sallis, J.F., McKenzie, T.L., Kolody, B., Lewis, M., Marshall, S., & Rosengard, P. (1999). Effects of health-related physical education on academic achievement: Project SPARK. Research Quarterly for Exercise and Sport, 70, 127-134. doi:10.1080/02701367.1999.1060 8030 Shephard, R.J. (1996). Habitual physical activity and academic performance. Nutrition Reviews, 54(4 Pt. 2), S32-S36. doi:10.1111/j.1753-4887.1996.tb03896.x Shephard, R.J. (1997). Curricular physical activity and academic performance. Pediatric Exercise Science, 9(2), 113-126. Shephard, R.J., & Trudeau, F. (2008). Research on the outcomes of elementary school physical education. The Elementary School Journal, 108, 251-264. Shephard, R.J., Volle, M., Lavallee, H., Labarre, R., Jequier, J.C., & Rajic, M. (1984). Required physical activity and academic grades: A controlled longitudinal study. In J. Ilmarinen & I. Valimaki (Eds.), Children and sport (pp. 58-63). Berlin: Springer Verlag. Stroth, S., Hille, K., Spitzer, M., & Reinhardt, R. (2009). Aerobic endurance exercise benefits memory and affect in young adults. Neuropsychological Rehabilitation, 19, 223-243. doi:10.1080/09602010802091183 Trost, S. (2009). Active education: Physical education, physical activity and academic performance. Retrieved from the Active Living Research website: http://activelivingresearch.org/active-education-physical-education-physical-activity-and-academic-performance Trost, S.G., & van der Mars, H. (2009/2010). Why we should not cut P.E. Educational Leadership, 67(4), 60-65. Trudeau, F., & Shephard, R.J. (2008). Physical education, school physical activity, school sports and academic performance. The International Journal of Behavioral Nutrition and Physical Activity, 5(10). Retrieved from http://www.ijbnpa.org/content/5/1/10. doi:10.1186/1479-5868-5-10 U.S. Department of Health and Human Services. (1996). Physical activity and health: A report of the Surgeon General. Retrieved from http://www.cdc.gov/nccdphp/sgr/pdf/sgrfull.pdf U.S. Department of Health and Human Services. (2011). Healthy people 2020 objectives. Retrieved from http://www.healthypeople.gov Weinstein, A.M., & Erickson, K.I. (2011). Healthy body equals healthy mind. Generations, 35(2), 92-98. Wilcock, A.A. (2007). Occupation and health: Are they one and the same? Journal of Occupational Science, 14(1), 3-8. doi:10.1080/144 27591.2007.9686577 Wilson, L., & Wilcock, A. (2005). Occupational balance: What tips the scales for new students? British Journal of Occupational Therapy, 68, 319-323.
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O
ne of the national objectives set by Healthy People 2020 is to increase the amount of moderate to vigorous physical activity people engage in daily to improve their health, fitness, and quality of life (U.S. Department of Health and Human Services [HHS], 2011). However, more than 80% of adults and youth do not meet the required standards for moderate and vigorous physical activity associated with improved health (HHS, 1996). For adults, regular physical activity is known to lower the risk of coronary heart disease, type 2 diabetes, stroke, and some types of cancer. For children
and adolescents, regular physical activity has been shown to improve bone health, improve cardiorespiratory and muscular fitness, and decrease levels of body fat. Additionally, for adults and adolescents, regular physical activity is associated with reduced symptoms of depression (HHS, 1996). Therefore, the impact of regular physical activity at a moderate to vigorous level has been clearly linked to improved health and well-being (HHS, 1996; McMurrer, 2007). Physical activity has also been linked to academic achievement in children (Ploughman, 2008; Trost & van der Mars, 2009/2010). However, since
Dr. Gonzalez is Assistant Professor, Occupational Therapy Program, The University of Texas at El Paso, El Paso, Texas; Ms. Hernandez is Occupational Therapist, Aprendamos Intervention Team, Las Cruces, New Mexico; Ms. Coltrane is Occupational Therapist, Texas Children’s Hospital, Houston, Texas; and Ms. Mancera is Pediatric Occupational Therapist, Easter Seals of West Georgia, Columbus, Georgia. Submitted: August 2, 2013; Accepted: June 30, 2014; Posted online: July 25, 2014 The authors have no financial or proprietary interest in the materials presented herein. This study was conducted with the approval of the Institutional Review Board at the University of Texas at El Paso. Address correspondence to Eugenia C. Gonzalez, PhD, OTR, 6611 Boeing, El Paso, TX 79925; e-mail: [email protected]. doi:10.3928/15394492-20140714-01
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the No Child Left Behind Act was enacted in 2002, more than 62% of elementary schools and 20% of middle schools increased the instructional time allotted to reading and math (Trost, 2009; Trost, & van der Mars, 2009/2010). Increased instruction time in math and reading was matched with reductions in time allocated to the liberal arts and physical education (Trost & van der Mars, 2009/2010). Lee, Burgeson, Fulton, and Spain (2007) reported that based on a nationwide survey of schools, only 3.8% of elementary schools, 7.9% of middle schools, and 2.1% of high schools offered daily physical education (PE) for the entire school year. The assumption being that by reducing time spent in extracurricular activities and increasing time spent on academics, students would demonstrate an improvement in academic performance. However, there is emerging evidence that reducing physical activity may be counterproductive to improving academic performance. In a longitudinal study done in Quebec, Canada, elementary school students were assigned to different levels of PE per week (Shephard, 1996, 1997; Shephard & Trudeau, 2008; Trudeau & Shephard, 2008). Students were assigned to participate in either 40 minutes of physical activity per week (control group) or 5 hours of physical activity per week (experimental group). Children in the experimental group scored higher than children in the control group on provincial examinations (i.e., annual academic examinations given to students in Canada). However, the experimental group scored higher than the control group only on the math portion of the examination, not the English portion. These results were interesting given that students in the experimental group were pulled out of their math classes to exercise but not pulled out of their English classes (Shephard et al., 1984). From a review of recent literature, Trost and van der Mars (2009/2010) reported that research conducted to investigate the effect of physical activity on academic performance, cognition, IQ, and standardized tests on elementary students supports the hypothesis that physical activity improves academic performance. Although not all studies identified in the literature have resulted in a positive effect of physical activity on academic performance, none of the studies reviewed reported a negative effect of physical activity on academic performance (Ahamed et al., 2007; Sallis et al., 1999). Evidence for the positive association between physical activity and academic performance is also present for students in middle and high school. Nelson and Gordon-Larsen (2006) had students in grades 7 to 12 participate in moderate to vigorous physical
activity five or more times weekly. Although they were investigating the effects of increased physical activity on risky behaviors and self-esteem, they also examined the effect of physical activity on academic achievement. Students in the group that participated in moderate to vigorous physical activity were more likely to earn an A grade in math or science than students who were less active. The Nelson and GordonLarsen (2006) study, therefore, provides evidence of the positive effects of physical activity on the academic performance of middle and high school students. However, no other studies related to physical activity and academic performance for this age group were identified by these authors. Studies that have used cognitive function as an outcome measure have also provided support for the positive association between physical activity and academic performance. Davis et al. (2011) used cognitive and academic achievement measures to study the effect of different doses of physical activity, specifically aerobic exercise, for children who were overweight and sedentary. They concluded that there was an effect of dose or level of physical activity such that children who participated in the highest dose of physical activity demonstrated the greatest improvement in executive function. Additionally, Davis et al. (2011) conducted functional magnetic resonance imaging (MRI) measures of brain activity during executive function tasks for a subset of their participants. They reported that the MRI data provided evidence that physical activity increased the prefrontal cortex activity bilaterally and decreased posterior parietal cortex activity; the combined action contributed to improved ability to plan ahead, inhibit inappropriate behaviors, and delay gratification. Therefore, they concluded that physical activity has an effect on academic performance by way of these brain systems that are directly related to cognition and behavior. The findings reported by Davis et al. (2011) are consistent with cognitive changes reported for older adults. From a meta-analysis of studies with older adults, Colcombe and Kramer (2003) concluded that aerobic fitness training also increases executive function in older adults (55 and older). This was especially true for executive control processes such as planning, inhibition, and scheduling of mental procedures (e.g., responding to a central or relevant cue while suppressing a response to an irrelevant cue presented simultaneously). More recent studies of healthy older adults have also provided support for the positive association between moderate to vigorous physical activity and improved cognitive function (Lautenschlager et al., 2008; Masley, Roetzheim, & Gualtieri, 2009).
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Additionally, from a review of the literature related to physical activity and cognitive function of older adults, Weinstein and Erickson (2011) concluded that physical activity enhances brain function as well as protects the brain against age-related decline associated with physiological changes present with normal aging. Studies in their review used structural and functional MRIs of human brains to examine changes related to physical activity. Their review included epidemiological, cross-sectional, and experimental studies. Overall, fitness levels have been linked to improved cognitive function and decreased risk for developing age-related cognitive problems (Weinstein & Erickson, 2011). From a review of studies on college students’ physical activity, Keating, Guan, Piñero, and Bridges (2005) reported that studies have been primarily focused on description of physical activity patterns and determinants of physical activity participation for this population. The second most common area of research with college students has focused on intervention studies to increase physical activity among college students. Research related to the relationship between physical activity and academic achievement or cognitive function of college students appears to be lacking. An exception is a survey study of undergraduate college students reported by Flynn, Coe, and Ode (2010). They reported that students who participated in vigorous physical activity 7 days per week had grade point averages (GPAs) four-tenths of a point higher (on a scale of 0 to 4) than those who did not participate in vigorous physical activity (Flynn et al., 2010). Although research with college students is limited, results of Flynn et al.’s (2010) study were consistent with results reported for younger students. Even though the role of student extends from childhood to adulthood, the demands and challenges of this occupation vary at different stages of education. Graduate school introduces a rigor and demand for excellence that is typically not present at the undergraduate level. Given the high academic standards and the importance of accurately learning the high volume of information needed for future application with vulnerable populations, students may find themselves placing greater emphasis on studying at the cost of balancing activities that include health behaviors such as exercise/fitness. The demands of occupational therapy programs and other professional programs may make it more difficult for students to maintain a healthy balance of occupations, roles, and leisure activities. Anecdotally, graduate students often report they were able to maintain a comfortable balance of roles, occupa-
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tions, and activities as undergraduates that they are not able to achieve as graduate students. Therefore, the purpose of this study was to examine the relationship between physical activity and GPA for graduate students enrolled in allied health programs at one college of health sciences in a university along the Texas-Mexico border. We hypothesized that the positive correlation between GPA and moderate to vigorous physical activity reported for younger students would also be present for graduate students enrolled in health sciences programs. The questions to be answered were: 1. What percentage of allied health graduate students report they participate in vigorous, moderate, or no physical activity? 2. Does physical activity level have a significant positive correlation with GPA for graduate students? 3. Are there differences in level of physical activity reported based on participants’ gender, ethnicity, or type of program in which the student is enrolled?
Method Research Design This was a retrospective study of graduate students’ self-reported physical activity and one marker of academic performance, GPA. Surveys were distributed to students in the participating health science programs during the same week before the end of the spring semester. Permission was attained from professors in each program to distribute the surveys at the beginning or end of a scheduled class. This strategy ensured all students in a cohort were contacted. Students were asked to sign a consent form that explained the study and confirmed that they could refuse to participate without penalty. Students then had the option to complete the International Physical Activity Questionnaire (IPAQ) short form and a demographic questionnaire. Surveys were labeled with the study number and separated from signed consent forms to ensure students’ information remained confidential. This study was conducted with the approval of the University Institutional Review Board. Participants Graduate students enrolled in health science programs at the University were asked to participate in the study. Participating programs included occupational therapy, physical therapy, speech language pathology, rehabilitation counseling, and pharmacy. Participation was limited to these programs because they share a common class-
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room building to hold environmental influences on physical activity constant. The University has a primarily Hispanic student body that reflects the population of the region. Measures International Physical Activity Questionnaire (Short Form). The IPAQ short form is a 7-item self-report measure of physical activity (IPAQ, 2005). The tool was designed for population surveillance of physical activity for people ages 15 to 69. It can be selfadministered or completed in a telephone/interview format. The IPAQ assesses physical activity undertaken in four domains: leisure time physical activity, domestic and gardening activities, workrelated physical activity, and transport-related physical activity. Participants are asked about walking, moderate-intensity activities, and vigorous-intensity activities undertaken within the four domains outlined above. The IPAQ short form can typically be completed in 10 minutes. The IPAQ short form has been reported to be a good measure of vigorous activity with moderate correlations to maximal oxygen uptake (VO2max), r = 0.41, p ≤ 0.01 (Kurtze, Rangul, & Hustvedt, 2008). The selected metabolic equivalent of task (MET) values used in the classification algorithm were derived from an IPAQ reliability study (Craig et al., 2003) and based on the Ainsworth et al. (2000) compendium. A MET is the ratio of work metabolic rate to a standard resting metabolic rate (Ainsworth et al., 2000). From international studies of the reliability and validity of the IPAQ, test-retest reliability for the short form has been reported as acceptable, with correlation coefficients ranging from 0.88 to 0.32 (Craig et al., 2003). Concurrent validity between the short and long forms was reported as good (pooled p = 0.67, 95% confidence interval [CI] 0.64, 0.70). Criterion validity of the short form was established by comparing selfreported activity against actual activity measured using Computer Science and Application’s Inc. accelerometers and was determined to be fair (p = 0.30, 95% CI 0.23, 0.36) (Craig et al., 2003). Both categorical and continuous scores can be derived from the IPAQ short form (IPAQ, 2005). The scoring algorithm provided for the IPAQ short form was used to classify participants’ reported physical activity as low, moderate, or high intensity (categorical scores). The MET values and formula for computation of MET-minutes/week provided in the IPAQ guidelines were used to calculate the total physical activity MET-minutes/week for continuous scores. (Data processing and scoring criteria are available online at http://www.ipaq.ki.se/scoring.pdf).
Demographic Questionnaire. This is a 6-item questionnaire developed for this study to gather demographic information and self-reported academic progress. Students were asked to report their age, gender, ethnicity, college of enrollment, and projected graduation date. They were also asked to report their current GPA to the nearest hundredth decimal point (i.e., 0.00). Statistical Analysis Data were analyzed using SPSS version 20. Guidelines proposed by the IPAQ Research Committee were used for data cleaning and processing the current data set (IPAQ, 2005) as follows: 1. All duration responses were recorded as minutes per day. 2. Cases with missing data or reported as “I don’t know or not sure” were removed from analysis. 3. Cases in which sum of any time variable was greater than 960 minutes (16 hours) were also excluded (assume 8 hours/day is spent sleeping). 4. Responses of less than 10 minutes were recoded as zero as recommended (because bouts of at least 10 minutes are required to achieve health benefits). 5. The times reported for walking, moderate, and vigorous activity participation that were greater than 180 minutes were truncated to be equal to 180 minutes. This was recommended to normalize the distribution of activity levels, which tend to be skewed in national or large population data sets (IPAQ, 2005).
Results There were 102 surveys distributed, and 100 were returned for analysis (98% return rate). The sample was primarily female (73%) and Hispanic (62%). Most students (42%) were in the third semester of their program. Characteristics of participants by program of study are reported in Table 1. Only surveys with complete data were entered into all analyses reported. GPA was the most common omission (six women and two men). Items left blank on the IPAQ were treated as missing data rather than coded as a zero response. Therefore, the smallest number of surveys available for statistical analyses was 81 (79%). GPAs ranged from 2.50 to 4.00 with a mean of 3.62 (SD = 0.29). Only two students reported a GPA lower than the 3.00 expected in graduate school. It is likely that these students were in their first semester of their program and enrolled on a probationary status and were therefore dropped from further analyses. An analysis of variance (ANOVA) for differences in mean GPAs based on the student’s program of study was
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Table 1 Characteristics of Graduate Students by Program of Study Gender Program of Study (n)
Ethnicity
Male
Female
Hispanic
Whitea
Blacka
Asian/Other
OT (19)
4 (21%)
15 (79%)
10 (53%)
5 (26%)
0 (0%)
4 (21%)
PT (27)
11 (41%)
16 (59%)
15 (56%)
9 (33%)
1 (4%)
2 (7%)
SLP (33)
5 (15%)
28 (85%)
21 (64%)
6 (18%)
1 (3%)
5 (15%)
Rehab. counseling (11)
3 (27%)
8 (73%)
10 (91%)
1 (9%)
0 (0%)
0 (0%)
Pharmacy (10)
4 (40%)
6 (60%)
6 (60%)
1 (10%)
1 (10%)
2 (20%)
Total sample (100)
27 (27%)
73 (73%)
62 (62%)
22 (22%)
3 (3%)
13 (13%)
Note. n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling. a Not of Hispanic origin.
not significant, F (4, 87) = 0.519, p = 0.722. Therefore, all students’ GPAs and self-reported physical activity levels were analyzed as an entire group rather than by program of study. GPA for the sample (N = 92) with the outliers removed was 3.64 (SD = 0.25). Overall, graduate students in this study reported physical activity at each level of intensity: low, moderate, and high. However, there were differences in the pattern of physical activity participation based on the program of study. For example, rehabilitation counseling had almost all students reporting vigorous-intensity physical activity and none reporting low-intensity physical activity. A nonparametric test for differences of frequencies within each level for the total sample was not significant. In other words, the difference in number of students participating at each level of intensity was not statistically significant (p = 0.067). The primary hypothesis was that there would be a positive relationship between physical activity and GPA for graduate students in this study. However, there was no correlation between physical activity and GPA when examined as three levels of physical activity (i.e., low, moderate, high), Spearman’s rho = –0.13, p = 0.128. Reported physical activity levels were also analyzed as continuous scores (IPAQ, 2005). The correlation between IPAQ continuous scores and GPA was also not significant at the 0.05 level (Pearson r = –0.12, p = 0.152). The two IPAQ score formats (categorical and continuous) were used in the analysis (ANOVA) to determine whether reported physical activity levels differed by gender, ethnicity, or program of study for this sample. No statistically significant difference was found in either the categorical or continuous scores based on gender: categorical score,
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F (1, 98) = 1.896, p = 0.172; continuous score, F (1, 98) = 1.391, p = 0.241. There was also no statistically significant difference in either the categorical or continuous scores based on participants’ ethnicity: categorical score, F (4, 94) = 0.636, p = 0.638; continuous score, F (4, 94) = 0.440, p = 0.779. However, a statistically significant difference was found in the categorical and continuous scores based on participants’ program of study: categorical score, F (4, 95) = 3.815, p = 0.006; continuous score, F (4, 95) = 5.003, p = 0.001. Continuous and categorical scores were significantly different between students in the rehabilitation counseling program and students in the other programs. Table 2 indicates the reported level of physical activity (categorical score) participation by program, and Table 3 shows total physical activity MET-minutes/week (continuous score) by program.
Discussion The current study was prompted by studies of physical activity and its relationship with academic performance because graduate students are concerned with their academic success. A common belief is that improving academic performance comes at the cost of reducing time for and resources spent on extracurricular activities that encourage physical activity. Therefore, future studies need to address other benefits of physical activity for students in professional programs. For example, from a study of medical students in different stages of their medical training, Jamali et al. (2013) reported that participation in daily physical activity was significantly associated with higher physical component scores derived from the 36-
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Table 2 Level of Physical Activity by Program and for Total Sample Program of Study (n) OT (19)
Low
Moderate
High
Minimum
Maximum
2 (11%)
8 (42%)
9 (47%)
1
3
PT (27)
7 (26%)
9 (33%)
11 (41%)
1
3
SLP (33)
12 (37%)
11 (33%)
10 (30%)
1
3
Rehab. counseling (11)
0 (0%)
1 (9%)
10 (91%)
2
3
Pharmacy (10)
3 (30%)
4 (40%)
3 (30%)
1
3
Total sample (100)
24 (24%)
33 (33%)
43 (43%)
1
3
Note. n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling.
Table 3 Mean Total Physical Activity MET-Minutes/Week by Program Program of Study (n)
Mean (SD)
Minimum
Maximum
OT (19)
3606.42 (2342.03)
0
8478
PT (27)
2296.43 (1841.05)
0
5958
SLP (33)
2470.27 (2587.25)
0
8892
Rehab. counseling (11)
5919.27 (2609.28)
1485
10158
Pharmacy (10)
3115.05 (3501.19)
0
10638
Total sample (100)
3083.07 (2663.39)
0
10638
Note. MET = Metabolic Equivalent of Task values; n = number of students in program who completed surveys; OT = occupational therapy; PT = physical therapy; SLP = speech language pathology; Rehab counseling = rehabilitation counseling.
item Short Form Health Survey. Additionally, scores on all eight of the quality of life domains they measured declined significantly as the stage of the medical student’s education became more difficult (Jamali et al., 2013). The contribution of physical activity to quality of life for graduate college students may be more closely related to achieving occupational balance. For example, Wilson and Wilcock (2005, p. 320) asked beginning-level occupational therapy students the question: “What prevents you from reaching occupational balance?” The primary analysis resulted in three themes—people, time, and money factors as main impediments. Further analysis of the “people” factor, not surprisingly, included factors such as value systems, priorities, motivation, and willpower, as well as skills, knowledge, and level of enjoyment. It was also evident from their analysis of students’ responses that fitness, diet, and health are important factors to consider in attaining occupational balance (Wilson & Wilcock, 2005).
When discussing occupational balance, it is often found that engaging in meaningful occupations brings forth greater quality of life. A vision of occupational therapy is to enhance the well-being of all populations and is not limited to people with disabilities (Wilcock, 2007). Therefore, future studies are needed to explore the factors that impede or facilitate participation for students in the health fields in the level of physical activity that provides the health and academic benefits reported in the literature. From a review of research related to the physical activity of college students, Keating et al. (2005) concluded that changing the sedentary patterns of college students will require collaboration between experts in physical education, exercise physiology, and health. Occupational therapy can provide invaluable insight for future intervention studies related to occupational balance and quality of life. As a former patient of one of the authors once stated, “You have to take care of yourself to be healthy enough to take care of others.”
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Limitations Null findings from the current study may have been related to the lack of sensitivity of the measure used to mark academic performance, GPA. Although a positive association between moderate to vigorous physical activity and GPA has been reported for school-age children and undergraduate students, the range of scores for that population is greater than for graduate students. Undergraduate college students’ grades can range from 0.0 to 4.0. However, at the graduate level, students’ GPA cannot drop below 3.0. This restricted the range in variability of the academic measure used for the current study. Although studies of the relationship between physical activity and academic performance of graduate students were not identified, there have been studies reporting a positive association between brain function and physical activity for older adults. However, these studies have used more precise measures of brain structures and brain function rather than GPA. For example, Weinstein and Erickson (2011) reviewed studies that used structural and functional MRIs of adults’ brains to measure changes associated with participants’ fitness levels. Likewise, Stroth, Hille, Spitzer, and Reinhardt (2009) reported that exercise seems to decrease tissue loss in brain areas relevant to executive control. They recorded increased levels of brain-derived neurotropic factor (BDNF) in adult animal brains after exercise. BDNF is known to be active in the brain areas needed for learning, memory, and higher thinking (i.e., hippocampus, cortex, basal forebrain). Specifically, they reported that changes in BDNF levels were associated with more efficient, plastic, and adaptive cognitive function that is demonstrated as improved learning and performance in adult animals. Although Stroth et al. (2009) reported age-related changes in animal models, their findings have implications for human beings as well. Another limitation of the current study is that admission into the programs included in the study are highly competitive. Therefore, students admitted into those programs have developed skills and strategies that may sufficiently moderate academic performance (as measured by GPA) to mask the effects of nonparticipation in regular physical activity. This competitive quality may also be what influences graduate students’ choice to dedicate a greater amount of time to studying instead of maintaining a healthful balance of activities. The five programs included in the study share an emphasis on patient care. However, there are differ-
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ences in the way the different programs are structured, making it possible that these differences are enough to influence students’ choices to participate in physical activity or not. For example, only the occupational therapy and physical therapy students complete four of their science courses together. These two programs and the speech language pathology program progress students in a lock-step manner so that students in these three programs complete their program with the same cohort. Therefore, students in these three programs do not have choices about the sequence or timing of classes they complete. This was also true for the pharmacy students, with the added requirement of completing their coursework at two different campuses in the state. Students in the rehabilitation counseling program were the only ones not in a lock-step program. This offered them flexibility in the type and amount of classes they completed each semester. This difference may have contributed to the fact that rehabilitation counseling students reported higher levels of physical activity. We chose not to analyze data for each program separately. This was done to reduce the threat of not having sufficient power to detect a difference if in fact one was present in the population. All the professional programs at this college of health sciences have low student-to-faculty ratios. Therefore, it was not possible to recruit more students. Increasing the number of participants from each department in the analysis would require data collection over several years, which would introduce additional threats to validity. Changing to more sensitive measures of academic achievement/performance, as indicated above, would be a preferred solution to this limitation.
Conclusions These data did not support the hypothesis that level of physical activity is associated with GPA for graduate students enrolled in allied health programs. Previous studies have confirmed a positive association between academic achievement and level of physical activity for younger students. There was a trend in the expected direction in that the one program whose students all reported moderate to vigorous physical activity levels was also the only program whose students reported 4.0 GPAs. However, measuring the effects of physical activity on cognitive function of graduate students may require a multidimensional approach that accounts for the interplay of the person’s characteristics and skills, the environmental demands, and their level of occupational performance.
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