AJCN. First published ahead of print March 25, 2015 as doi: 10.3945/ajcn.115.110221.
Editorial
Are active video games useful to combat obesity?1–3 Tom Baranowski There has been a lot of interest in active video games (AVGs),4 sometimes called exergames, as a source of physical activity (PA). AVGs were originally designed and sold as an entertainment medium with the objective of making a profit. Members of the public health and kinesiology communities saw the potential to increase PA by using AVGs. A key issue is whether AVGs, which generally (but not always) promote indoor/in-home PA, would be useful in combating the obesity epidemic. In-home activity has generally been ignored by obesity prevention interventions, thereby perhaps providing a unique niche for AVGs, especially for children who live in unsafe neighborhoods and are not allowed outside to play. Some of the recent reviews of PA from AVGs have held out hope of positive outcomes (1), and some have been less than enthusiastic (2). A substantial number of articles documented that most AVGs can result in a player’s engaging in moderate to vigorous PA in the laboratory, but concern has been expressed about whether AVGs resulted in PA under more natural circumstances (3). One study showed that simply providing 2 AVGs to children resulted in no documented increase in PA (4), whereas at least 2 others showed that the use of AVGs contributed to a reduction in BMI (5, 6). Within this maelstrom of apparently conflicting findings, substantial energy intakes were documented during AVG play (7, 8), suggesting that AVGs might contribute to obesity, not prevent it. Furthermore, a theory (9) and evidence (10) were presented that PA (of any kind) performed earlier in a day is compensated with less PA later in the day or the next day. In this context, Gribbon et al. (11) conducted an important study, the first to clearly place AVG play within an energy balance framework, addressing both the energy intake and energy expenditure (EE) sides of balance. They hypothesized that the increased EE from AVG play would be compensated both by energy intake and by ensuing reductions in PA (EE). The authors recruited 13- to 17-y-old male adolescents but used a substantial number of exclusionary criteria, which limits generalizability. The sample was relatively small (n ¼ 36), which limits the authors’ ability to make statements about lack of differences across conditions. A crossover design was used. Although the time between conditions (1–4 wk) would be long enough to attain washout in a pharmaceutical trial, one wonders what effects on behavior in later conditions might have occurred from memory of earlier conditions. However, random sequencing should minimize these possible effects. Participants were assigned to 1 of 3 exposures (1 h rest, 1 h entertainment game play,
1 h AVG play) on alternating days separated by 1–4 wk. EE was measured during the three 1-h experimental exposures by using a metabolic analyzer. PA was measured on the day of each exposure and for the 3 ensuing days by using accelerometers from which EE was estimated; diet was also measured. Consistent with many other studies, the authors reported substantially increased PA EE during AVGs but not for the 24 h of the experiment, nor for the 3 ensuing days. There were no betweengroup differences in dietary intake during the experimental period, the 24 h, or the ensuing 3 days. In most considerations, the substantial increase in PA EE during AVG play would be considered supportive of using AVGs for promoting PA. The lack of increased caloric intake during AVG play, in combination with the increased PA, would ordinarily suggest that AVGs could be useful in addressing obesity. The authors, however, concluded the reverse. Their argument hinged on the lack of statistically significant between-group differences in EE during the 24 h including the experiment as evidence for compensation, thereby limiting the value of AVGs. At this point, the authors appear to have forgotten their own citations of the literature that compensation occurs for all PA; should we not encourage any activity because compensation occurs? Furthermore, the measurement of 1 From the USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX. 2 Primarily funded by several grants, including “Using Technology to Prevent Obesity among African American Girls” (MD005814) from the National Center for Minority Health and Disease; “Video Games for Obesity & Diabetes Prevention: Efficacy Trial2 (DK091254-01) from the National Institute of Diabetes Digestive and Kidney Diseases; “Kiddio Food Fight: Training Parents in Effective Vegetable Parenting” (HD075521) from the National Institute of Child Health and Human Development; “Minimizing Memory Errors in Child Diet Assessment” (CA 172864) from the National Cancer Institute; “Narrative Impact of Active Video Games on Physical Activity” (CA158917) from the National Cancer Institute; and “Motivational Theatre to Increase Vegetable Intake in Children” (HD073608) from the National Institute of Child Health and Human Development. This work is also a publication of the US Department of Agriculture, funded in part with federal funds from the USDA/ARS under Cooperative Agreement number 3092-5-001-058. 3 Address correspondence to T Baranowski, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Department of Pediatrics, 1100 Bates Street, Houston, TX 77030-2600. E-mail: tbaranow@bcm. edu. 4 Abbreviations used: AVG, active video game; EE, energy expenditure; PA, physical activity. doi: 10.3945/ajcn.115.110221.
Am J Clin Nutr doi: 10.3945/ajcn.115.110221. Printed in USA. Ó American Society for Nutrition
Copyright (C) 2015 by the American Society for Nutrition
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EDITORIAL
EE during the experiment, when differences were detected, was made directly with a Cosmed K4b2 metabolic analyzer (a precise measure of EE), whereas the measurement of PA with ensuing EE estimation during the 24-h period was made with an Actical accelerometer (Philips Respironics), which is not a precise measure of EE. The significant between-group difference in EE during the hour of AVG versus non-AVG play appears to have been ;700 kJ (from looking at their Figure 3). The statistically nonsignificant between-group difference (AVG play group higher) during the 24 h appears to have been ;500 kJ (from looking at their Figure 4). The small sample size and lower-quality estimated EE measure for the 24-h period put limits on when authors can claim lack of differences. At this time, it appears likely that opposing scientists will continue to believe what they want, in turn determining how they interpret the Gribbon et al. results. It is hoped that this study will be replicated by other groups, with larger samples, betweengroup designs, and perhaps more consistent measures (e.g., all accelerometry). It would also be valuable to test the compensation ideas under more naturalistic circumstances. Research has identified a variety of enhancements that could be incorporated that would likely increase PA from AVGs (12, 13). Recent innovations in games in general and in AVGs in particular have been astounding. New technology (e.g., sensors) may come bundled with AVGs that further enhance their PA potential, when we learn how best to use them. For example, the AVG that used the Kinect sensor (Microsoft) in the Gribbon et al. study appears to have resulted a substantially higher increase in PA than with earlier AVGs that used game controllers (3). It has been difficult for researchers to stay ahead of the possible contributions of the many innovations that are occurring with AVGs. Some of us believe that the future of AVGs to enhance PA is bright, but the research needs to clarify the extent of, and limits on, their contribution. We can’t assume “If they build it, kids will be active.” The author had no conflicts of interest to report.
REFERENCES 1. Lu AS, Kharrazi H, Gharghabi F, Thompson D. A systematic review of health games on childhood obesity prevention and intervention. Games Health J 2013;2:131–41. 2. Chaput JP, Leblanc AG, McFarlane A, Colley RC, Thivel D, Biddle SJ, Maddison R, Leatherdale ST, Tremblay MS. Active Healthy Kids Canada’s position on active video games for children and youth. Paediatr Child Health 2013;18:529–32. 3. Barnett A, Cerin E, Baranowski T. Active video games for youth: a systematic review. J Phys Act Health 2011;8:724–37. 4. Baranowski T, Abdelsamad D, Baranowski J, O’Connor TM, Thompson D, Barnett A, Cerin E, Chen T-A. Impact of an active video game on healthy children’s physical activity. Pediatrics 2012; 129:e636–42. 5. Maddison R, Foley L, Ni Mhurchu C, Jiang Y, Jull A, Prapavessis H, Hohepa M, Rodgers A. Effects of active video games on body composition: a randomized controlled trial. Am J Clin Nutr 2011;94: 156–63. 6. Trost SG, Sundal D, Foster GD, Lent MR, Vojta D. Effects of a pediatric weight management program with and without active video games a randomized trial. JAMA Pediatr 2014;168:407–13. 7. Lyons EJ, Tate DF, Ward DS, Wang X. Energy intake and expenditure during sedentary screen time and motion-controlled video gaming. Am J Clin Nutr 2012;96:234–9. 8. Mellecker RR, Lanningham-Foster L, Levine JA, McManus AM. Energy intake during activity enhanced video game play. Appetite 2010;55: 343–7. 9. Fr´emeaux AE, Mallam KM, Metcalf BS, Hosking J, Voss LD, Wilkin TJ. The impact of school-time activity on total physical activity: the Activitystat hypothesis (EarlyBird 46). Int J Obes (Lond) 2011;35: 1277–83. 10. Ridgers ND, Timperio A, Cerin E, Salmon J. Compensation of physical activity and sedentary time in primary school children. Med Sci Sports Exerc 2014;46:1564–9. 11. Gribbon A, McNeil J, Jay O, Tremblay MS, Chaput J-P. Active video games and energy balance in male adolescents: a randomized crossover trial. Am J Clin Nutr 2015;101;■■–■■. 12. Baranowski T, Maddison R, Maloney A, Medina E Jr., Simons M. Building a better mousetrap (exergame) to increase youth physical activity. Games Health J 2014;3:72–6. 13. Baranowski T. Games for increasing physical activity: mechanisms for change. Games Health J 2015;4:1–2.
Editorial
Are active video games useful to combat obesity?1–3 Tom Baranowski There has been a lot of interest in active video games (AVGs),4 sometimes called exergames, as a source of physical activity (PA). AVGs were originally designed and sold as an entertainment medium with the objective of making a profit. Members of the public health and kinesiology communities saw the potential to increase PA by using AVGs. A key issue is whether AVGs, which generally (but not always) promote indoor/in-home PA, would be useful in combating the obesity epidemic. In-home activity has generally been ignored by obesity prevention interventions, thereby perhaps providing a unique niche for AVGs, especially for children who live in unsafe neighborhoods and are not allowed outside to play. Some of the recent reviews of PA from AVGs have held out hope of positive outcomes (1), and some have been less than enthusiastic (2). A substantial number of articles documented that most AVGs can result in a player’s engaging in moderate to vigorous PA in the laboratory, but concern has been expressed about whether AVGs resulted in PA under more natural circumstances (3). One study showed that simply providing 2 AVGs to children resulted in no documented increase in PA (4), whereas at least 2 others showed that the use of AVGs contributed to a reduction in BMI (5, 6). Within this maelstrom of apparently conflicting findings, substantial energy intakes were documented during AVG play (7, 8), suggesting that AVGs might contribute to obesity, not prevent it. Furthermore, a theory (9) and evidence (10) were presented that PA (of any kind) performed earlier in a day is compensated with less PA later in the day or the next day. In this context, Gribbon et al. (11) conducted an important study, the first to clearly place AVG play within an energy balance framework, addressing both the energy intake and energy expenditure (EE) sides of balance. They hypothesized that the increased EE from AVG play would be compensated both by energy intake and by ensuing reductions in PA (EE). The authors recruited 13- to 17-y-old male adolescents but used a substantial number of exclusionary criteria, which limits generalizability. The sample was relatively small (n ¼ 36), which limits the authors’ ability to make statements about lack of differences across conditions. A crossover design was used. Although the time between conditions (1–4 wk) would be long enough to attain washout in a pharmaceutical trial, one wonders what effects on behavior in later conditions might have occurred from memory of earlier conditions. However, random sequencing should minimize these possible effects. Participants were assigned to 1 of 3 exposures (1 h rest, 1 h entertainment game play,
1 h AVG play) on alternating days separated by 1–4 wk. EE was measured during the three 1-h experimental exposures by using a metabolic analyzer. PA was measured on the day of each exposure and for the 3 ensuing days by using accelerometers from which EE was estimated; diet was also measured. Consistent with many other studies, the authors reported substantially increased PA EE during AVGs but not for the 24 h of the experiment, nor for the 3 ensuing days. There were no betweengroup differences in dietary intake during the experimental period, the 24 h, or the ensuing 3 days. In most considerations, the substantial increase in PA EE during AVG play would be considered supportive of using AVGs for promoting PA. The lack of increased caloric intake during AVG play, in combination with the increased PA, would ordinarily suggest that AVGs could be useful in addressing obesity. The authors, however, concluded the reverse. Their argument hinged on the lack of statistically significant between-group differences in EE during the 24 h including the experiment as evidence for compensation, thereby limiting the value of AVGs. At this point, the authors appear to have forgotten their own citations of the literature that compensation occurs for all PA; should we not encourage any activity because compensation occurs? Furthermore, the measurement of 1 From the USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX. 2 Primarily funded by several grants, including “Using Technology to Prevent Obesity among African American Girls” (MD005814) from the National Center for Minority Health and Disease; “Video Games for Obesity & Diabetes Prevention: Efficacy Trial2 (DK091254-01) from the National Institute of Diabetes Digestive and Kidney Diseases; “Kiddio Food Fight: Training Parents in Effective Vegetable Parenting” (HD075521) from the National Institute of Child Health and Human Development; “Minimizing Memory Errors in Child Diet Assessment” (CA 172864) from the National Cancer Institute; “Narrative Impact of Active Video Games on Physical Activity” (CA158917) from the National Cancer Institute; and “Motivational Theatre to Increase Vegetable Intake in Children” (HD073608) from the National Institute of Child Health and Human Development. This work is also a publication of the US Department of Agriculture, funded in part with federal funds from the USDA/ARS under Cooperative Agreement number 3092-5-001-058. 3 Address correspondence to T Baranowski, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Department of Pediatrics, 1100 Bates Street, Houston, TX 77030-2600. E-mail: tbaranow@bcm. edu. 4 Abbreviations used: AVG, active video game; EE, energy expenditure; PA, physical activity. doi: 10.3945/ajcn.115.110221.
Am J Clin Nutr doi: 10.3945/ajcn.115.110221. Printed in USA. Ó American Society for Nutrition
Copyright (C) 2015 by the American Society for Nutrition
1 of 2
2 of 2
EDITORIAL
EE during the experiment, when differences were detected, was made directly with a Cosmed K4b2 metabolic analyzer (a precise measure of EE), whereas the measurement of PA with ensuing EE estimation during the 24-h period was made with an Actical accelerometer (Philips Respironics), which is not a precise measure of EE. The significant between-group difference in EE during the hour of AVG versus non-AVG play appears to have been ;700 kJ (from looking at their Figure 3). The statistically nonsignificant between-group difference (AVG play group higher) during the 24 h appears to have been ;500 kJ (from looking at their Figure 4). The small sample size and lower-quality estimated EE measure for the 24-h period put limits on when authors can claim lack of differences. At this time, it appears likely that opposing scientists will continue to believe what they want, in turn determining how they interpret the Gribbon et al. results. It is hoped that this study will be replicated by other groups, with larger samples, betweengroup designs, and perhaps more consistent measures (e.g., all accelerometry). It would also be valuable to test the compensation ideas under more naturalistic circumstances. Research has identified a variety of enhancements that could be incorporated that would likely increase PA from AVGs (12, 13). Recent innovations in games in general and in AVGs in particular have been astounding. New technology (e.g., sensors) may come bundled with AVGs that further enhance their PA potential, when we learn how best to use them. For example, the AVG that used the Kinect sensor (Microsoft) in the Gribbon et al. study appears to have resulted a substantially higher increase in PA than with earlier AVGs that used game controllers (3). It has been difficult for researchers to stay ahead of the possible contributions of the many innovations that are occurring with AVGs. Some of us believe that the future of AVGs to enhance PA is bright, but the research needs to clarify the extent of, and limits on, their contribution. We can’t assume “If they build it, kids will be active.” The author had no conflicts of interest to report.
REFERENCES 1. Lu AS, Kharrazi H, Gharghabi F, Thompson D. A systematic review of health games on childhood obesity prevention and intervention. Games Health J 2013;2:131–41. 2. Chaput JP, Leblanc AG, McFarlane A, Colley RC, Thivel D, Biddle SJ, Maddison R, Leatherdale ST, Tremblay MS. Active Healthy Kids Canada’s position on active video games for children and youth. Paediatr Child Health 2013;18:529–32. 3. Barnett A, Cerin E, Baranowski T. Active video games for youth: a systematic review. J Phys Act Health 2011;8:724–37. 4. Baranowski T, Abdelsamad D, Baranowski J, O’Connor TM, Thompson D, Barnett A, Cerin E, Chen T-A. Impact of an active video game on healthy children’s physical activity. Pediatrics 2012; 129:e636–42. 5. Maddison R, Foley L, Ni Mhurchu C, Jiang Y, Jull A, Prapavessis H, Hohepa M, Rodgers A. Effects of active video games on body composition: a randomized controlled trial. Am J Clin Nutr 2011;94: 156–63. 6. Trost SG, Sundal D, Foster GD, Lent MR, Vojta D. Effects of a pediatric weight management program with and without active video games a randomized trial. JAMA Pediatr 2014;168:407–13. 7. Lyons EJ, Tate DF, Ward DS, Wang X. Energy intake and expenditure during sedentary screen time and motion-controlled video gaming. Am J Clin Nutr 2012;96:234–9. 8. Mellecker RR, Lanningham-Foster L, Levine JA, McManus AM. Energy intake during activity enhanced video game play. Appetite 2010;55: 343–7. 9. Fr´emeaux AE, Mallam KM, Metcalf BS, Hosking J, Voss LD, Wilkin TJ. The impact of school-time activity on total physical activity: the Activitystat hypothesis (EarlyBird 46). Int J Obes (Lond) 2011;35: 1277–83. 10. Ridgers ND, Timperio A, Cerin E, Salmon J. Compensation of physical activity and sedentary time in primary school children. Med Sci Sports Exerc 2014;46:1564–9. 11. Gribbon A, McNeil J, Jay O, Tremblay MS, Chaput J-P. Active video games and energy balance in male adolescents: a randomized crossover trial. Am J Clin Nutr 2015;101;■■–■■. 12. Baranowski T, Maddison R, Maloney A, Medina E Jr., Simons M. Building a better mousetrap (exergame) to increase youth physical activity. Games Health J 2014;3:72–6. 13. Baranowski T. Games for increasing physical activity: mechanisms for change. Games Health J 2015;4:1–2.
