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Original Research
Physical Activity and Screen Time Sedentary Behaviors in College Students
1 South Dakota State University, Brookings, SD, USA 2 Department of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, USA
‡Denotes professional author, †Denotes graduate student author
ABSTRACT Int J Exerc Sci 4(2) : 102-112, 2011. It is well established that Americans are not meeting physical activity (PA) guidelines and college students are no exception. Given the lack of regular PA, many health promotion professionals seek to discover what barriers to PA may exist. A common explanation is screen time (ST), which is comprised primarily of television viewing, computer use, and the playing of video games. The purpose of this study was to present descriptive data on college students’ PA and sedentary behavior and to assess if any evidence exists to suggest displacement between sedentary behaviors and PA in college students. Students completed an online health survey specific to time spent in PA and sedentary behavior. Students were categorized into one of three PA groups based on their activity level. Males were significantly more physically active than females in terms of days per week engaged in aerobic exercise (p=.022) and strength training (p<.001). When categorized by activity level, a greater percentage of male students met recommended PA levels than did females (p<.001). Males reported significantly higher levels of overall ST (p=.004) and television viewing (p<.001), whereas females reported significantly higher levels of time spent engaged in homework (p<.001). When categorized by activity level, physically active students reported significantly fewer minutes of total ST than inactive students (p=.047). Implications of this study suggest that within a college population, television and PA are not competing behaviors in either gender.
KEY WORDS: Sedentary behavior, physical inactivity, displacement hypothesis

College is a time of great change for young adults. Newly found independence allows the college student to make decisions and choices that were often previously made for him or her. One of the most important decisions a college student may make is how to incorporate physical activity (PA) into a busy lifestyle. According to the 2008

National College Health Assessment, 18% of college students engage in PA five or more days per week, with 23.3% reporting zero physical activity in the last seven days (1). Recent recommendations from the 2008 Physical Activity Guidelines for Americans (43) suggest that low levels of PA are a major health concern. With so few college students participating in PA, researchers


seek to determine what activities may potentially be supplanting PA.
The U.S. Department of Labor publishes the American Time Use Survey (ATUS) which collects information on how people living in America spend their time. Data from the 2008 ATUS showed that weekday leisure time for full time university and college students totaled 3.67 hours (44). When leisure time is categorized, television viewing comprises the largest percentage, at 1.84 hours per day, or about half of all leisure time (44). Television is unquestionably a sedentary activity, and many studies have hypothesized that increases in television viewing may be partly to blame for reductions in PA (3, 11, 18).
Overall, sedentary behavior is perceived to have increased in the past decade, in large part due to increased computer and internet usage (30, 41). Screen time, defined operationally as time spent using computers, watching television or DVDs, and/or playing video games (29), may be heavily influenced in college students by the recent popularity of social networking sites such as Facebook and Twitter. Prior estimates of computer usage by college students are limited and range widely from 2.8 hours per week (44) to 11.6 hours per week (2). Nonetheless, much like the noncollege adult population (44), it appears that a significant amount of college students’ leisure time is spent on screen time sedentary behaviors.
One of the more popular explanations of how screen time may be negatively influencing PA is the displacement hypothesis (4). The displacement hypothesis posits a symmetrical, zero-sum

relationship in which the more time an individual devotes to screen time, the less time the individual will have to devote to PA (32). Another tenet of the displacement hypothesis is that the finite nature of time budgets requires the introduction of new activities and behaviors to force out old activities and behaviors (32). As screen time has increased over the past two decades, there has been a concomitant decrease in PA, contributing to an increased prevalence of obesity, especially in youth and adolescents (22, 27, 49). If screen time is somehow replacing PA, then this relationship may be explained by the displacement hypothesis. Specific to inactive college students, the displacement hypothesis postulates that an increase in sedentary behaviors, such as television viewing, computer usage, or video game playing, will be associated with a concomitant decrease in PA. Although the claims of the displacement hypothesis are often cited by many authors, empirical evidence supporting a negative relationship between PA and screen time is lacking (28). How sedentary behaviors may influence PA has yet to be fully explained (5).
Despite the fact that 18.2 million young adults are enrolled in colleges and universities (42), little is known about their PA and sedentary habits (20, 25). Previous research on the relationship between PA and sedentary behavior has been indeterminate in children (28, 39, 45), college students (37), and adults (16). Therefore, the purpose of this study was twofold. First was to present descriptive data on college students’ PA and sedentary behavior and to examine for gender differences within these variables. Second was to assess if any evidence exists to

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suggest displacement between sedentary behaviors and PA in college students.


Participants A sample of 736 students (461 male, 275 female, 62.1 % freshmen, mean age 19.11 ± 2.04 years) were recruited from two university required wellness courses at a Midwestern university. This study was approved by the university’s Institutional Review Board (IRB). Students who participated in this study signed an informed-consent form prior to participation in accordance with IRB policies. All students 18 years of age or older, and enrolled in either of the two wellness courses, were invited to participate.


Anthropometric measurements of height

and weight were recorded for each

participant. Height was measured to the

nearest .5 cm with a Seca #214 portable

stadiometer. Weight was measured with a

calibrated Tanita Digital TBF-215GS scale to

the nearest .1 Kg. Additionally, participants

completed a comprehensive online health

survey consisting of questions concerning

dietary habits, PA, and sedentary pursuits.

The participants were directed by their

respective class instructor to complete the

online health survey using the




management system. Participants were

given one week to complete the survey

outside of class.

Survey questions are presented in Figure 1. The first two questions, specific to PA, were based on a previously validated questionnaire, the Youth Risk Behavior

Surveillance System (YRBSS) (7). Response choices for each question ranged from zero to seven days. The third PA question was based upon a recently validated 5-response (PA5) single response survey to assess stages of change (21). The five stage of change categories were merged into three categories for data analysis: Inactive (precontemplation and contemplation), Insufficiently Active (preparation), and Active (action and maintenance). This merging allowed the data to be compared to a pre-established PA standard from the Centers for Disease Control and Prevention/American College of Sports Medicine (35). The stage of change methodology is consistent with the public health indicators used for tracking progress toward Healthy People 2010 standards (10).
Time spent in sedentary behaviors was assessed by three novel questions developed by the authors and validated in unpublished pilot testing. Responses for all three sedentary behavior questions were recorded in minutes. For sedentary behaviors, 24 hour recall was used instead of, “in the past 7 days” or “on average” as it has been shown to produce better recall and greater reliability with a large sample (23, 47).
Statistical Analysis Data were analyzed via Statistical Package for the Social Sciences (SPSS) for Windows, version 18.0. Descriptive statistics were computed for various demographic variables (i.e. age, BMI, PA, sedentary behaviors). Independent samples t-tests were used to examine for differences in means between genders. Chi-square tests were used to examine for differences in proportions between the genders. Three separate 2 (gender) X 3 (stage of change

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category) between-subjects ANOVAs were used to examine for differences in screen time, television time, and homework minutes. Scheffe post-hoc comparisons were used to determine the location of significant differences across the stage of change categories. Alpha was set at p ≤ 0.05 for all analyses.
In the past seven days, on how many days did you engage in aerobic physical activity or exercise other than casual walking?
In the past seven days, on how many days did you engage in strength building or resistance exercise?
Which of the following statements best describes your current level of physical activity or exercise, including walking for exercise?
a) I don’t exercise or walk regularly now and I don’t plan to start in the near future.
b) I don’t exercise or walk regularly now but I’ve been thinking about starting.
c) I’m doing moderate physical activity fewer than five times per week or vigorous activity fewer than three times a week.
d) I’ve been doing moderate physical activity five or more days a week or vigorous activity at least three days a week for the last one to six months.
e) I’ve been doing moderate physical activity five or more days a week or vigorous activity at least three days a week for seven months or longer.
Yesterday, how much time, in minutes, did you spend in front of a screen? (This includes computer, television, video games, movies, etc.)
Of your total screen time yesterday, how much of it, in minutes, was spent watching television?
Yesterday, how many minutes did you spend on school work outside of class? (i.e. homework) Figure 1. Physical Activity/Sedentary Behavior Survey Questions.
Independent samples t-tests were used to examine for differences in PA, sedentary

behaviors, and body mass index (BMI) (Table 1). Male students were older and had a higher BMI than female students. In addition, male students reported significantly more days of aerobic exercise, strength training, screen time, and television minutes compared to female students. Female students reported more time spent on homework compared to males.
Chi square tests were used to analyze the distribution of stage of change categories (Table 2). Of all students, 43.5% met recommended levels of PA, as represented by the Active stage (action and maintenance). A greater percentage of male students met recommended PA levels than did females. A greater percentage of females were classified as Inactive or Insufficiently Active than males.
Mean minutes (± SD) of homework, screen time, and television viewing are shown in Table 3 and stratified by stage of change category. Factorial ANOVA results indicated no significant main effects for stage of change when television viewing time and homework minutes were analyzed as separate dependent variables. Additionally, no significant gender by stage of change interactions were found when television viewing time, screen time, and homework minutes were used as individual dependent variables. However, when analyzing screen time, a significant main effect for stage of change was found, F (2, 730) = 4.95, p = 0.007. Scheffe post-hoc tests revealed that active students reported significantly fewer minutes of screen time than inactive and insufficiently active students (p=0.047 and p=0.032, respectively).

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Table 1. Descriptive Characteristics of College


Variable Total



t value P





19.10±2.04 19.35±2.37 18.69±1.24 4.937 < .001


Body Mass Index

24.05±4.22 24.34±4.30 23.56±4.06 2.436 .015

Aerobic Exercise (d/wk)



3.04±1.93 2.298 . 021

Strength Training (d/wk)



1.13±1.42 6.514 < .001

Screen Time (min)

144.60± 104.25

153.18± 108.71

130.21± 94.54

2.918 < .001

TV Time (min)

61.26± 67.08

69.39± 70.73

47.62± 58.08

4.529 < .001

Homework (min)

96.55±84.9 4


115.92±93. 15


< .001

Note. The p values indicate between gender


Table 2. Physical


Stage of






Activity Stage

9.8% (n=45)

16.7% (n=46)

of Change



7.714 .005

Insufficiently 44.2% 40.6% 50.2% 6.462 .011


(n=325) (n=187) (n=138)


43.5% (n=320)

49.7% (n=229)

33.1% (n=91)

19.277 < .001

Note. The p values indicate the difference between male and female responses.


habits and patterns of college students. As the current generation of college students is purported to have a sharp increase in internet usage (6), this study sought to determine how much time students spend in sedentary or inactive pursuits, as represented by screen time and daily homework.

Table 3. Sedentary Behaviors by Stage of Change.




n = 91


n = 320

n = 325















Screen Time (min)
Male Female Total
Homework (min)
Male Female Total

183.11±140.46 140.87±82.67 161.76±116.25a
83.02±85.65 86.85±66.08 84.96±75.99

167.67±106.86 132.59±104.01 152.78±106.92a
84.29±75.35 117.36±97.30 98.33±86.78

135.47±100.53 121.21±84.72 131.42±96.38
85.97±77.83 128.44±96.08 98.05±85.45

The second objective of this study was to assess if the data collected provides any evidence of sedentary behaviors displacing PA in college students. This is relevant because many interventions that are designed to increase PA invariably target a reduction in sedentary behaviors in hopes of increasing PA (24). However, for this assumption to be true, PA and sedentary behaviors would have to be competing behaviors, as posited by the displacement hypothesis.

The primary purpose of this study was to gather descriptive data on college students in regard to PA and sedentary behavior. Descriptive data concerning the above behaviors is quite limited within the literature; therefore, a major goal was to address the lack of research on the activity

Within this study, male students reported significantly higher levels of PA than did female students, as represented by days per week of aerobic exercise (3.37 vs. 3.04), days of strength training (1.90 vs. 1.13), and by the stages of change categories that reflect recommended levels of PA (49.6% vs.

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33.1%). The gender difference in PA demonstrated within this investigation is consistent with previous studies in multiple age cohorts which have reported that males are consistently more active than females (8, 9). Previous studies examining PA stage of change in college students have found that 50% of students do not meet recommended levels of PA (25). However the distribution of PA stage of change has been inconsistent in terms of gender (36, 48). In terms of total aerobic exercise, levels from this study (3.25 days per week) fall somewhere between the 3.41 days per week reported by Buckworth and Nigg (5) and the 2.8 days per week reported by Huang et al. (20). Students from this study did report fewer days dedicated to strength training (1.61 days per week) than shown in previous research (2.16 and 2.2 days per week, respectively) (5, 20). Collectively, the variations in reported PA may be representative of the limitations of the sample used, whether or not students were recruited from a physical education class, and perhaps most importantly, how PA was assessed. In this study, cross sectional surveys were used instead of more objective measures, such as accelerometers (13). However, a particular strength of this study was that participants were representative of the entire student body as the courses used for recruitment were a graduation requirement for all students, representing over 100 different academic majors on campus, resulting in a large sample size and results similar to previous ACHA assessments (1).
In regard to sedentary behavior, this study found, on average, that students spent 144 minutes per day dedicated to screen time, with 60 minutes spent watching television. Collectively, students from this study also

reported 96 minutes per day spent on homework, although a significant gender gap was noted between males and females (85 min vs. 115 min, p <0.001). In this study, when compared to their female peers, male students reported significantly higher levels of overall screen time and time spent viewing television, whereas female students reported significantly higher levels of time spent engaged in homework.
The market research firm Student Monitor found that college students watched television 11.2 hours per week (26), a number that is comparable to the 10.56 hours per week reported by Buckworth and Nigg (5). Data from the Harvard School of Public Health’s College Alcohol Study found students reported an average of two hours of television per day (33), which pales in comparison to a study by Nielsen Media Research (34), conducted during 2004-2005 which showed college students watched an average of 24.3 hours of television per week. Students in this study watched less television (approximately one hour per day, or seven hours weekly) than did those in the above studies. One possible explanation for this discrepancy is this study’s use of 24 hour recall versus the global time estimates used in the comparison studies. Global time estimates, which are commonly used in cross sectional research, have a tendency to overestimate time spent within a given behavior, whereas 24 hour recall results in higher quality data in terms of validity (23). Specific to this study, almost 90% of responses are representative of a weekday, with more than 60% of all responses reflecting Tuesday and Wednesday.

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Previous studies utilizing cross sectional

estimates of college student computer use

have ranged widely, from less than three

hours to more than 11 hours per week (2, 5,

44). The present study did not directly

measure computer use, but given the 16.8

hours per week of screen time reported (of

which seven hours was dedicated to

television viewing), an estimate of nearly

10.5 hours per week may be attributed to

computers, which falls within the

previously reported range.


measurement of computer use is still in its

relative infancy, so this study contributes

additional insight into how much time

college students are actually spending on


The second aim of this study was to assess if any evidence exists that may suggest screen time based sedentary behaviors may displace PA. Contrary to conventional wisdom, this study provides evidence that PA and television viewing may not be competing behaviors. Regardless of gender or PA participation, when students were categorized according to their PA stage of change, there was no significant difference in the amount of television watched. This finding suggests that if a college student chooses to watch television, it may not come at the expense of being physically active. In essence, a college student has the option to partake in both behaviors if he or she so chooses. Given this finding, this study calls into question the tenet of the displacement hypothesis that suggests choosing PA versus television is an either or choice.

Specific to this study, the displacement hypothesis would theorize that when sedentary behaviors such as television viewing increase, PA will subsequently

decrease; therefore television effectively displaces PA (32). This displacement hypothesis is an assumption that is very common within the literature, despite contrary findings by Marshall et al. (28). Biddle et al. take a harder stance against the displacement hypothesis suggesting that although watching television is prohibitive of PA at that time, one should not assume that television is thus negatively associated with PA over an entire day (4). If PA and inactivity are in fact separate constructs (12, 40), efforts to increase PA based on a competing behaviors model may prove to be unsuccessful. The present study tends to agree with the more recent literature, indicating that while multiple behaviors do exist, there appears to be little competition for PA time.
In terms of sedentary behaviors, when classified by PA stage of change, a distinction was made between television viewing and screen time as a whole. Specifically, no significant differences existed between the stages of change categories for television viewing time; however, inactive and insufficiently active students reported significantly more minutes of screen time than active students. If television does not displace PA, other modes of screen time may be contributing to the low levels of PA. Vandewater et al. (46) found that video game use among children was linked to reductions in PA. This may imply that various modes of screen time may in fact be independent of each other. Whereas television may not have any effect upon PA, evidence from this study suggests non-television related screen time, such as recreational computer use and video games, are associated with lower levels of PA.

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Limitations of this study include not differentiating between screen time for academic purposes versus screen time for leisure pursuits and the use of recall, especially for screen time. Nonetheless, 24 hour recall has been shown to be quite reliable in large samples (44). As for leisure and academic screen time, some crossover is inevitable. Also, with no objective measurement of PA, the possibility of overreporting exists. An additional limitation is that this study did not account for text messaging as a part of screen time. Whereas previous research examining text messaging has typically focused on the magnitude of texts sent each day (31), a recent study by the Kaiser Family Foundation indicated that junior and senior high students average 1:35 hours per day text messaging (38). However, due to the sporadic and multi-tasking nature of text messaging, a valid and reliable method of capturing this behavior has not been established. Pilot studies conducted by the authors and subsequent interviews of subjects concluded the ability to quantify text messaging was not feasible for this study.
In summary, male students were significantly more physically active than their female counterparts when assessed by days per week spent engaged in aerobic exercise and strength training. Male students also reported significantly higher levels of overall screen time and television viewing, whereas female students reported significantly higher levels of time spent engaged in homework.
Implications of this study suggest that within a college population, television and PA are not competing behaviors in either gender. These findings are important for

several reasons. First, future research in this area may be aided by utilizing a time diary or media log to record behaviors when they occur in real time rather than relying on recall. Several studies have utilized 24 hour time diaries to determine when PA and sedentary behaviors occur over the course of a day (17, 19, 46, 47). When time data can be analyzed via blocks of time, the sensitivity of the assessment tool may allow the researcher to identify the exact duration and time in which a specified behavior occurred (17, 19). Second and more practically, is that developing and implementing interventions to promote PA based on reduced television time alone may not be as successful as if all screen time behaviors were considered.
1. American College Health Association. American College Health Association-National College Health Assessment: Reference Group Data Report Spring 2008. Baltimore, MD: American College Health Association; 2008.
2. Anderson KJ. Internet use among college students: An exploratory study. J Am Coll Health 50: 21-26, 2001.
3. Bar-Or O, Foreyt J, Bouchard C, Brownell KD, Dietz WH, Ravussin E, Salbe AD, Schwenger S, St. Jeor S, Torun B. Physical activity, genetic and nutritional considerations in childhood weight management. Med Sci Sports Exerc 30: 2–10, 1998.
4. Biddle SJH, Gorely T, Marshall SJ, Murdey I, Cameron N. Physical activity and sedentary behaviors in youth: Issues and controversies. J R Soc Promot Health 124: 29-33, 2003.
5. Buckworth J, Nigg C. Physical activity, exercise, and sedentary behavior in college students. J Am Coll Health 53: 28-34, 2004.
6. Budden CB, Anthony JF, Budden MC, Jones MA. Managing the evolution of a revolution: Marketing implications of internet media usage among college

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students. College Teaching Methods & Style Journal 3: 5-10, 2007.

7. Centers for Disease Control and Prevention. Methodology of the youth risk behavior surveillance system. MMWR Recomm Rep 53(No. RR-12): 1-13, 2004.

8. Centers for Disease Control and Prevention. Youth risk behavior surveillanceUnited States, 2005. MMWR Surveill Summ 55(No. SS-5): 1-108, 2006.

9. Centers for Disease Control and Prevention. Prevalence of regular physical activity among adults — United States, 2001 and 2005. MMWR Morb Mortal Wkly Rep 56: 1209-1212, 2007.

10. Centers for Disease Control and Prevention.

Physical activity resources for health professionals:

An explanation of US physical activity surveys. May




s/data/explanation.html. Accessed January 1, 2011.

11. Dietz WH, Strasburger VC. Children, adolescents, and television. Curr Probl Pediatr 21: 8– 31, 1991.

12. Dietz WH. The role of lifestyle in health: The epidemiology and consequences of inactivity. Proc Nutr Soc 55: 829-840, 1996.

13. Dinger MK, Behrens TK. Accelerometerdetermined physical activity of free-living college students. Med Sci Sports Exerc 38: 774-779, 2006.

14. Epstein LH, Roemmich JN. Reducing sedentary behavior: Role in modifying physical activity. Exerc Sport Sci Rev 29: 103-108, 2001.

15. Epstein LH, Roemmich JN, Paluch RA, Raynor HA. Physical activity as a substitute for sedentary behavior in youth. Ann Behav Med 29: 200-209, 2005.

16. Foster JA, Gore SA, West DS. Altering TV viewing habits: An unexplored strategy for Adult Obesity Intervention? Am J Health Behav 30: 3-14, 2006.

17. Fountaine CJ, Liguori G, Mozumdar A. The relationship among physical activity, television

viewing, computer use, and video game playing in college students. Int J Fit 6: 19-26, 2010.
18. Gortmaker SL, Dietz WH, Cheung LW. Inactivity, diet, and the fattening of America. J Am Diet Assoc 90: 1247-1252, 1990.
19. Hager RL. Television viewing and physical activity in children. J Adolesc Health 39: 656-661, 2006.
20. Huang T T-K, Harris KJ, Lee RE, Nazir N, Born W, Kaur H. Assessing overweight, obesity, diet, and physical activity in college students. J Am Coll Health 52: 83-86, 2003.
21. Jackson AW, Morrow JR, Bowles HR, FitzGerald SJ, Blair SN. Construct validity evidence for singleresponse items to estimate physical activity levels in large sample studies. Res Q Exerc Sport 78: 24-31, 2007.
22. Jackson DM, Djafarian K, Stewart J, Speakman JR. Increased television viewing is associated with elevated body fatness but not with lower total energy expenditure in children. Am J Clin Nutr 89: 1031-1036, 2009.
23. Juster FT. Response errors in the measurement of time use. J Am Stat Assoc 81: 390-402, 1986.
24. Kahn EB, Ramsey LT, Brownson RC, Heath GW, Howze EH, Powell KE, et al. The effectiveness of interventions to increase physical activity: A systematic review. Am J Prev Med 22(suppl 4): 73107, 2002.
25. Keating XD, Guan J, Pinero JC, Bridges DW. A meta-analysis of college students’ physical activity behaviors. J Am Coll Health 54: 116-125, 2005.
26. Kordela J. Collegians watching more TV. The Daily Aztec. November 21, 2004. Available at: Accessed April 7, 2008.
27. Lobstein TL, Baur L, Uauy R. Obesity in children and young people: A crisis in public health. Obes Rev 5(Suppl 1): 4-85, 2004.
28. Marshall SJ, Biddle SJH, Gorely T, Cameron N, Murdey I. Relationships between media use, body

International Journal of Exercise Science



fatness and physical activity in children and youth: A meta-analysis. Int J Obes 28: 1238-1246, 2004.

29. Marshall SJ, Gorely T, Biddle SJH. A descriptive epidemiology of screen-based media use in youth: A review and critique. J Adolesc 29: 333-349, 2006.

30. Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, Troiano RP. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol 167: 875-881, 2008.

31. Media Literacy Clearinghouse. Media use




Accessed December 29, 2010.

32. Mutz DC, Roberts DF, Vuuren DP. Reconsidering the displacement hypothesis: Television’s influence on children’s time use. Communic Res 20: 57-75, 1993.

33. Nelson TF, Gortmaker SL, Subramanian SV, Cheung L, Wechsler H. Disparities in overweight and obesity among US college students. Am J Health Behav 31: 363-373, 2007.

34. Nielsen Media Research. College students living

away from home to be included in national people







60aRCRD. Accessed April 7, 2008.

35. Pate RR, Pratt M, Blair SN, et al. Physical activity and public health: A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 273:402–407, 1995.

36. Pinto BM, Marcus BH. A stages of change approach to understanding college students' physical activity. J Am Coll Health 44: 27-31, 1995.

37. Prochaska JJ, Sallis JF, Sarkin JA, Calfas KJ. Examination of the factor structure of physical activity behaviors. J Clin Epidemiol 53: 866-874, 2000.

38. Rideout VJ, Foehr UG, Roberts DF. Generation M2: Media in the lives of 8-18 year-olds. Kaiser Family Foundation. January 2010. Available at: Accessed December 29, 2010.
39. Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc 32: 963-975, 2000.
40. Taveras EM, Field AE, Berkey CS, Rifas-Shiman SL, Frazier AL, Colditz GA, Gillman MW. Longitudinal relationship between television viewing and leisure-time physical activity during adolescence. Pediatrics 119: 314-319, 2007.
41. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 40: 181-188, 2008.
42. US Census Bureau. Statistical Abstract of the United States: 2008. 127th ed. Washington, DC: US Government Printing Office; 2007.
43. US Dept of Health and Human Services. 2008 Physical Activity Guidelines for Americans. Washington, DC: US Dept of Health and Human Services: 2008.
44. US Dept of Labor, Bureau of Labor Statistics. American Time Use Survey. Available at: Accessed July 3, 2009.
45. Van Der Horst K, Paw MJ, Twisk JW, Van Mechelen W. A brief review on correlates of physical activity and sedentariness in youth. Med Sci Sports Exerc 39: 1241-1250, 2007.
46. Vandewater EA, Shim M, Caplovitz AG. Linking obesity and activity level with children’s television and video game use. J Adolesc 27: 71-85, 2004.
47. Vandewater EA, Bickham DS, Lee JH. Time well spent? Relating television use to children’s free-time activities. Pediatrics 117: 181-191, 2006.
48. Wallace LS, Buckworth J, Kirby TE, Sherman WM. Characteristics of exercise behavior among college students: Application of social cognitive theory to predicting stage of change. Prev Med (Baltim) 31: 494-505, 2000.

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Screen TimeTelevisionActivityStudentsStudy