URC

Does Exergaming Achieve the Same Levels of Fitness Intensity as Unstructured Activity?

Courtney A. Graham
Rachel M. Perron
Jamie R. Feldman
Eric E. Hall*

Elon University, Elon, NC

Abstract

Exercise games were developed by video game designers to combat sedentary behavior. The purpose of this study was to explore the intensity levels of exergaming in comparison to an unstructured physical activity program. Sixteen female participants (Mean age=9.4 ± 1.0 years) spent twenty minutes in unstructured physical activity, monitored by a mentor, and twenty minutes playing exercise games on the Nintendo Wii™. Based on our findings, it can be concluded that only the WiiFit exergame can achieve intensity levels comparable to unstructured activity.

Introduction

The nationwide prevalence of obesity in all age groups has risen drastically over the past decades and is often attributed to the dramatic increase in sedentary behaviors as a result of the technology boom (Wang & Beydoun, 2007). It has been proposed that childhood and adolescence is the most critical period for the development of obesity, and such a proposition has made the prevention of obesity in children a public health priority (Wang & Lobstein, 2006).  It was noted that children’s play has moved from the streets and playgrounds to the couches and television screens. Specifically, recent studies showed that children spend two to five hours per day in front of television and/or computer screens (Vandewater, Bickham, & Lee, 2010). In fact, Anderson, Economos, and Must (2008) found that 61.5 percent of children in a nationally representative survey had not engaged in any organized physical activity outside of school in the previous 7 days, and 23 percent had not engaged in any physical activity at all.

Two factors that are believed to play a role in the increase in sedentary behavior in children are a perceived lack of neighborhood safety (Dixon et al., 2010; Farley et al., 2007) and a decreased level of physical activity in adults (Anderson, Economos, & Must, 2008). If parents do not perceive their neighborhood to be safe for children to play outside, they will discourage their children from playing in their front yards or on local playgrounds. Veitch and colleagues (2010) found that activity levels (as measured by accelerometers) were much higher for children whose parents perceived their neighborhood to be safe than for those that did not. Moreover, if parents are not setting an example for their children and engaging in physical activity themselves, there is a slim possibility that their children will have the motivation and the opportunity to be physically active and therefore will choose more sedentary activities (Anderson, Economos, & Must, 2008). Furthermore, physically inactive parents are less likely to enroll their children in physically engaging activities such as recreational sports due to their own lack of ability and interest.

A third and perhaps most influential factor in the increase in sedentary behaviors of children is the immense increase in technology over the past few decades. With the vast expansion of video game systems, sedentary game play has become a preferred method of play for many children. More children than ever before spend the majority of their playtime seated in front of a screen, an activity with incredibly detrimental consequences. Anderson and colleagues (2008) found that 77 percent of obese girls had high screen time as compared to their healthier counterparts. Screen time, according to the authors, is any time spent in front of a screen of any kind, be it a television, video game system, computer, or anything of that same nature. Furthermore, with the increased ability for social interaction on video games, children no longer have to depend on physical activities such as team sports and playground activities in order to develop relationships (Veitch, Salmon, & Ball, 2010). As a result, even less time is spent in unstructured active play and more time is spent engaging in sedentary video games.

The American College of Sports Medicine (ACSM, 2008) recommended that children engage in 60 minutes of moderate to vigorous activity daily. Furthermore, the guidelines recommend at least three days per week be spent engaging in physical activity that focuses on strengthening muscle and bone. The ACSM does not specify any precise ways in which children should attain the recommended 60 minutes of activity. In an effort to assuage the detrimental impacts of sedentary videogames on children’s health, video game researchers developed exercise games or exergames. These games attempt to get children off the couch and physically engaged while they participate in games on consoles such as the Nintendo WiiÔ. Many studies have shown that exergames played over short periods of time may be of similar in intensity to traditional physical activities such as walking, skipping, and jogging (Graf, Pratt, Hester, & Short, 2009).

Long-term interventions with active video games have shown their potential to improve body composition, cardiorespiratory fitness, and physical activity levels in overweight children (Maddison et al., 2009). Maddison et al. (2009) distributed over 150 active video game upgrade packages for the Sony Eye Toy® to children age 10-14. The children were encouraged to use the video games to meet the recommended daily amount of physical activity. It was found that over 12- and 24-month periods, the children who used active video games decreased their BMI, increased their cardiorespiratory fitness, and decreased their percent body fat. Dance Dance Revolution™ (DDR), a game initially popular in arcades but then made available for home use, has been demonstrated to engage players in moderate to vigorous levels of physical activity (Tan, Aziz, Chua, & Teh, 2002; Unnithan, Houser, & Fernhall, 2006). The game requires participants to follow patterns of arrows that occur on screen with full-body movement. As the arrows flash across the screen participants have to jump from the corresponding arrows on a dance pad located on the floor. In fact, a four-month intervention study found that children with access to DDR decreased sedentary screen time and increased vigorous physical activity levels more than children who did not have access to the exergame (Maloney et al., 2008).

Furthermore, acute interventions have shown that exergames can increase activity levels better than non-active video games. One study found that playing DDR for ten consecutive minutes at a difficulty of “medium” elicits heart rate ranges of 65-70 percent of heart rate maximum (Tan, Aziz, Chua, & Teh, 2002). Researchers recorded heart rate before participants engaged in a ten-minute session of medium-difficulty DDR songs and immediately following the ten minutes. They found not only that heart rate was elevated to within the ACSM’s recommended range for moderate activity but that participants’ rate of perceived exertion indicated that they felt as though the exercise was of moderate intensity as well. Another study found that playing ten minutes of WiiSports boxing elicited higher heart rates than ten minutes of treadmill walking at 1.5 miles per hour or ten minutes of non-active video game play (Penko & Barkley, 2010).

Additionally, it was found that both parents and children are interested in engaging in interactive video games as a means of obtaining physical activity (Dixon et al., 2010). In their study, Dixon and colleagues (2010) interviewed parents and children (ages 10-14) in 11 different focus groups after allowing them to play interactive video games such as the Sony Eye Toy® and Dance Dance Revolution™. Both children and parents reported feeling as though the games allowed them to engage in physical activity and were enjoyable as well.

Because so many children are now turning to sedentary behaviors such as video games instead of active forms of play, it is necessary to find a way in which to engage children’s interest as well as get them moving. The use of exergames could prove to be the link between the technology boom and increasing physical activity in children. The purpose of this study was to investigate the intensity levels of exergaming in comparison to unstructured activity to determine if exergames can be used as a viable intervention for increasing the amount of physical activity amongst children in the United States.

Methods

Participants

Thirteen girls (age = 9.4 ± 1.0 years, height = 56.2 ± 3.9 inches, weight = 108.3 ± 12.9 pounds) were recruited from the Alamance Girls in Motion program at a small southeastern university. Girls in Motion is a national eight-week program that seeks to address the issues of body image, self-esteem, and healthy eating for girls age 9-11. The goals of the program are to build a positive body image and self-esteem in young girls, prevent obesity and eating disorders, develop healthy attitudes about food and exercise, and utilize young women as positive role models and mentors for young girls (Girls in Motion, 2011). At the orientation session, parents were briefed on the experiences that their daughters would have if they chose to participate in the research. If the parents decided that their daughter could participate in the research, they signed informed consent forms that were approved by the University’s Institutional Review Board.

Measures of Exercise Intensity

Subjective measures of exercise intensity. The Borg Rating of Perceived Exertion (RPE) scale was used to measure perceived exertion. This scale ranges from 6-20, with 6 being “no exertion at all” and 20 being “maximal exertion” (Borg, 1998).

Objective measures of exercise intensity. Exercise intensity was measured with accelerometers and heart rate monitors. The accelerometer data was coded such that 60 second epochs of time for each condition was categorized as either light intensity or moderate intensity based on cut points determined by Freedson, Pober, and Janz (2005). Total minutes of light and moderate intensity exercise were summed for each of the games. Heart rate was recorded with a Polar heart rate monitor. Participants placed the monitors around their chest, and recording watches were worn around the wrist.

Procedures

Data collection was divided into two sessions, one lab session and one unstructured activity session. Participants were randomly selected to either participate in the lab session or the unstructured activity session first. Before the data collection began, height and weight were measured, and the participants were briefed on the activities in which they would be engaging.

The lab session consisted of participants playing two games on the WiiFit game (hula hoop and running) and two games on the WiiSports game (tennis and boxing). Before beginning their sessions, participants were fitted with a heart rate monitor (Polar, Lake Success, NY) and an accelerometer placed at the right hip (Actigraph model GTM1). Each participant spent ten minutes playing WiiFit and ten minutes playing WiiSports.  During the ten minutes, participants were allowed to randomly choose between two different activities that were determined by the researchers prior to the testing. At two different times (5 min during the activity and at the end of the activity), the participants were asked their rate of perceived exertion (Borg 1998). Additionally, the researchers recorded heart rate at three time periods (before the activity, 5 min during the activity, at the end of the activity).

The unstructured activity session involved a twenty-minute period of time in which the participant was with her mentor doing whatever activities she chose. The mentors were a selected group of female college students who agreed to participate in all eight weeks of the program and were individually assigned to the participants before the research began. Before their activity time began, halfway through their time (10 min.), and at the end of the twenty minutes, the mentors were instructed to record the heart rate. RPE was recorded at 10 minutes during the activity and the end of the activity. At the end of the twenty minutes, the mentors and their partners returned to the lab.

Data Collection

A Game (3: Wii Fit, WiiSports, unstructured activity) by Time (depending on variable) Repeated Measures General Linear Model (RM GLM) was used to determine main and interaction effects of condition and time (within-subjects repeated measure) for each of the variables.

Results

A 3 (Condition) x 3 (Time: pre, middle and post) RM GLM for heart rate revealed a significant condition effect (F (2, 11) = 20.02, p < .001), time effect (F (2, 11) = 77.12, p < .001), and condition*time interaction (F (4, 9) = 6.06, p = .012).  The condition effect was due to a greater heart rate during Wii Fit compared to unstructured activity (p = .023) and Wii Sports (p < .01). There was not a statistical difference between unstructured activity and Wii Sport (p = .070).  See Figure 1 for graphical analysis of data.

Figure 1. Heart rate vs. Time for the 3 Exercise Conditions
HR SURF.jpg

A 3 (Condition) x 2 (Time: middle and post) RM GLM for RPE showed a significant effect for time (F (1, 13) = 6.82, p = .022), but not for condition (F (2, 12) = 1.99, p = .179). No condition*time interaction was observed (F (2, 12) = 3.20, p = .077). The time effect was due to RPE being greater following exercise compared to during exercise (See Figure 2).

Figure 2. Ratings of Perceived Exertion vs. Time for the 3 Exercise ConditionsRPE SURF.jpg

A RM GLM found a significant difference for condition (F (2, 13) = 17.15, p < .001) that was due to greater moderate activity in the unstructured activity, 75.2 percent of minutes compared to Wii Fit, 66.1 percent of minutes (p < .001), and Wii Sports, 32.1 percent of minutes (p < .001). There was not a statistical difference between Wii Fit and Wii Sports (p = .091).

Discussion

 Based on our findings, the WiiFit exergame may be a superior exergame strategy to the Wii Sports exergame. Specifically, it was found that heart rate was highest at the end of the WiiFit session as opposed to the Wii Sports session. Additionally, it may be fair to assert that WiiFit may elicit physical activity participation of similar intensity to unstructured activity. Because the heart rates achieved during the WiiFit condition were higher than the unstructured activity session, it can be assumed that the WiiFit has similar overall benefits to the already known benefits of unstructured activity in children (Veitch, Salmon, & Ball, 2010). As such, parents can encourage their children to participate in exergames such as the WiiFit and have confidence that the children are working towards their recommended 60 minutes of moderate activity every day.  Additionally, exergames have the potential to be viable and enticing physical activity interventions for children.

Our findings indicate that the mean RPE for the participants in the WiiFit condition was 17, which is reflective of “moderately difficult.” Furthermore, the participants’ mean heart rate for the WiiFit condition was 170, which is roughly 80 percent of the age-predicted heart rate max for children of this age demographic. As such, our findings show that the WiiFit elicits heart rate intensities that are considered moderate to vigorous by the ACSM. These findings are similar to those found through the short-term DDR studies (Maloney et al., 2008; Tan, Aziz, Chua, & Teh, 2002).

Additionally, our findings supported the hypothesis that exergames such as the WiiFit can be used as an alternative to unstructured activity to help children achieve their recommended levels of physical activity. Our results showed that for both RPE and heart rate intensities, WiiFit time and unstructured activity time had similar values. These results are similar to those found by Graf and colleagues (2009), who reported that Wii Boxing and DDR were of comparable intensity to walking at a moderate pace. As such, children who need to improve their fitness for weight maintenance as well as those who need to engage in activity to maintain a healthy lifestyle can use exergames as a means to obtain their activity levels.

Because the current technology craze has led to a drastic increase in screen time, it is important that exercise interventions be geared toward technological advances (Dixon et al., 2010). Exergames such as the WiiFit allow for children to engage in video games yet also increase their energy expenditure and thus can be used to help combat the obesity epidemic. The findings of this study are similar to those of other studies that have shown that various exergames can help children achieve moderate to vigorous levels of physical activity (Tan, Aziz, Chua, & Teh, 2002; Unnithan, Houser, & Fernhall, 2006). Unnithan and colleagues (2006) showed the importance and relevance of exergames as physical activity interventions when they compared overweight to non-overweight children playing DDR. They found that overweight children who played DDR displayed higher energy expenditure levels than non-overweight children, thus demonstrating that exergames could help children get fit and maintain fitness levels (Unnithan, Houser, & Fernhall, 2006).

There are a few potential limitations to this study. Although significant differences were found amongst heart rates for the different conditions, it can be said that increasing the number of measurement points for heart rate would increase the validity of the results. With the collection of more heart rate data points (i.e., at every minute or with every change in activity), more specific results as to the role each game plays in overall physical exertion could be obtained. Furthermore, the placement of the accelerometers on the hip could have limited the measurement of overall body movements, as many Wii games primarily involve upper extremity movement that wouldn’t necessarily be picked up on the hip accelerometer (Choi, Chen, Acra, & Buchowski, 2010). Lastly, although all of the college mentors for the participants of Girls in Motion are given various topics to focus on each session, they are also given a lot of freedom in activity choice during their free-play time. As such, some participants spent their time walking, others spent it playing structured games such as volleyball, and still others spent their time doing seated activities. As a result, broad interpretations of energy expenditure during free time were made, and thus may not give an accurate depiction of unstructured activity.

Future studies may be warranted to address potential psychological benefits resulting from long-term exergame participation. Besides the various studies showing the potential physiological benefits of exergames, it has been shown that engaging in exergames provides a high level of motivation for otherwise inactive children. Specifically, it has been found that overweight children are equally motivated to play inactive video games and exergames (Penko & Barkley, 2010). Additionally, it is proposed that the novelty of exergames may provide more motivation than traditional outdoor activities such as walking, jogging, and skipping (Graf, Pratt, Hester, & Short, 2009). Lastly, it is proposed that exergames will provide children with an opportunity to try a wide range of activities that they might not otherwise experience. As such, children might be more likely to engage in the authentic activities and thus increase their physical activity levels (Daley, 2009). Thus, examining psychological factors such as affect and enjoyment of activities will provide information about children’s willingness to engage in exergames for an extended period of time.

Conclusions

It has been shown that the WiiFit exergame elicits physical activity levels similar to that of unstructured activity. As such, it is proposed that exergames such as the WiiFit can be used to help children achieve their recommended 60 minutes of daily physical activity. Additionally, the WiiFit game has been shown to improve other important aspects of motor development in children such as postural control and kinesthetic awareness (Fitzgerald, Trakarnratanakul, Smyth, & Caulfield, 2010). These findings could serve to help combat the current issue of physical inactivity amongst children and adolescents in an effective way, as well as improve children’s overall motor development and coordination.

References

Anderson, S.E., Economos, C.D., & Must, A. (2008). Active play and screen time in US children aged 4 to 11 years in relation to sociodemographic and weight status characteristics: A nationally representative cross-sectional analysis. BMC Public Health, 8, 366.

Borg, G. (1998). Borg's Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics.

Choi, L., Chen, K.Y., Acra, S.A., & Buchowski, M.S. (2010). Distributed lag and spline modeling for predicting energy expenditure from accelerometry in youth. Journal of Applied Physiology, 108(2), 314-327.

Daley, A. J. (2009). Can exergaming contribute to improving physical activity levels and health outcomes in children? Pediatrics, 124(2), 763-771.

Dixon, R., Maddison, R., Mhurchu, C.N., Jull, A., Meagher-Lundberg, P., & Widdowson, D. (2010). Parents’ and children’s perceptions of active video games: A focus group study. Journal of Child Health Care, 14(2), 189-199.

Farley, T.A., Meriwether, R. A., Baker, E.T., Watkins, L.T., Johnson, C.C., & Webber, L.S. (2007). Safe play spaces to promote physical activity in inner-city children: Results from a pilot study of an environmental intervention. American Journal of Public Health, 97(9), 1625-1631.

Fitzgerald, D., Trakarnratanakul, N., Smyth, B. & Caulfield, B. (2010). Effects of a wobble board-based therapeutic exergaming system for balance training on dynamic postural stability and intrinsic motivation levels. Journal of Orthopaedic and Sports Physical Therapy, 40(1), 11-19.

Freedson, P., Pober, D, & Janz, K.F. (2005). Calibration of accelerometer output for children. Medicine and Science in Sports and Exercise, 37 (11 Suppl.), S523-S530.

Girls In Moton. (2011). Mission Statement. Retrieved March 30, 2011, from Girls in Motion: www.girlsinmotion.org

Graf, D.L., Pratt, L.V., Hester, C.N., & Short, K.R. (2009). Playing active video games increases energy expenditure in children. Pediatrics, 124(2), 534-540.

Maddison, R., Foley, L., Mhurchu, C.N., Jull, A., Jiang, Y., Prapavessis, H., Rodgers, A., Vander Hoorn, S., Hohepa, M., & Schaaf, D. (2009). Feasability, design, and conduct of a pragmatic randomized controlled trial to reduce overweight and obesity in children: The electronic games to aid motivation to exercise (eGAME) study. BMC Public Health, 9(146).

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Penko, A.L., & Barkley, J.E. (2010). Motivation and physiologic responses of playing a physically interactive video game relative to a sedentary alternative in children. Annals of Behavioral Medicine, 39, 162-169.

Tan B., Aziz A. R., Chua K., Teh K.C. (2002). Aerobic demands of the dance simulation game. International Journal of Sports Medicine, 23(2), 125-129.

Unnithan V. B., Houser W., Fernhall B. (2006). Evaluation of the energy cost of playing a dance simulation video game in overweight and non-overweight children and adolescents. International Journal of Sports Medicine, 27, 804-809.

Vandewater, E.A., Bickham, D.S. & Lee, J.H. (2006). Time well spent? Relating television use to children’s free time activities. Pediatrics, 117(2), 181-191.

Veitch, J., Salmon, J., & Ball, K. (2010). Individual, social and physical environmental correlates of children’s active free-play: A cross-sectional study. International Journal of Behavioral Nutrition and Physical Activity, 7(11).

Wang, Y., & Beydoun, M.A. (2007). The obesity epidemic in the United States – gender, age, socioeconomic, racial/ethnic, and geographic characteristics: A systematic review and meta-regression analysis. Epidemiologic Reviews, 29, 6-28.

Wang, Y. & Lobstein, T. (2006). Worldwide trends in childhood overweight and obesity. International Journal of Pediatric Obesity, 1, 11-25.

 

Note: We would like to thank Professor Liz Bailey for her willingness to let us recruit participants and mentors from her Girls in Motion program.

                                                                                                  


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