Gaming Health: A Goals-Means-Agency Framework for Evaluating and Designing Physical Activity Games

Cynthia Carter Ching, University of California Davis
Roxanne Rashedi, University of California Davis
and Sara Elizabeth Schaefer, University of California Davis

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Abstract

Childhood obesity is prevalent in the United States, affecting 12.7 million individuals and comprising roughly 17% of children and youth ages 2-19 (CDC, 2011). In the past, technology and video games have been blamed for childhood obesity and accompanying sedentary behavior patterns (Gordon-Larson et al, 2004; Vandewater, et al, 2004). Certainly, video games as a pastime are ubiquitous among young people; about 99% of boys and 94% of girls play them (Lenhart, 2008). Currently, however, researchers and designers are attempting to harness the motivational power of digital games to help improve players’ physical health (Lu, 2013; Oh & Yang, 2010). Yet such games are often lumped into a single category of “exergames” and evaluated for their overall effectiveness at impacting narrow health indicators (Wylie & Coulton, 2008). Instead, we argue, a more nuanced approach is necessary to evaluate the means and goals of physical activity games, and, perhaps most importantly, we also need a different way of thinking about the role of players in relation to these games and to their own health and behavior.

As such, this essay serves two functions. First, building on but also challenging Baranowski’s (2008) model, we propose a framework for examining a commercial and research marketplace full of vastly different physical activity games. Our framework is driven by the following questions: (1) What is the evidence of various health games on sustainable behavior change? (2) What kinds of theoretical frameworks can researchers, educators, and/or players use to inform which game(s) they decide to use? (3) And what set of principles and/or aspects do such games have? Drawing on social cognitive and narrative theories (Bandura, 1986; Bamberg, 2011), we review the components, characters, and genres of various physical activity gaming technologies to identify the principles of games that are likely to best promote behavioral changes over extended periods of time. We analyze examples of commercially available exergames and healthy gaming applications and discuss how these games can, on the one extreme, create medical or behaviorist “treatments” that position players as the objects of technological intervention, or, on the opposite end of the spectrum, provide fun and engaging ways for players to gain agency and grow aware of their own health data. Second, our paper describes a game developed by our research team (created in collaboration with professional game designers and junior high school students) that explicitly serves this latter type of agency goal. We provide an overview of Terra, a sci-fi exploration game that syncs players’ wearable physical activity monitor data and converts it into “energy” that players can use for game action. Our discussion will identify the principles of this game-based system that promote authentic engagement and student agency, such that we are concerned primarily with not only young players’ behavior, but also their insights about the role of physical activity in their everyday lives.

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Essay

“Gaming the system” is a phrase commonly used to indicate a process of actively manipulating a situation toward some maximally beneficial outcome, even if (or especially if) the manipulations in question constitute a breach of the system’s rules, constraints, or predictable behavior. Learning scholars argue that the ability to generate strategies for gaming in this way indicates a profound understanding of the system parameters in question, as well as a high degree of agency relative to one’s role within the system itself (Salen, Gresalfi, Peppler, & Santo, 2014). When it comes to health, however, the meaning of who or what is being gamed can vary dramatically. Some kinds of health gaming designs or interventions have as their goal the active manipulation of players, essentially tricking players into engaging in healthy behavior they would otherwise avoid. Other approaches, however, are designed to have the player use the game as a tool to help them make beneficial health decisions and expose what may be hard-to-see behavior patterns or motivations holding them back. So the question then becomes: Is the player the agent or the object of the game? The answer, as we will argue in this paper, is complicated.

Childhood obesity is prevalent in the United States, affecting 12.7 million individuals and comprising roughly 17% of children and youth ages 2-19 years (Ogden, Carroll, Kit, & Flegal, 2014). In the past, technology and video games have been blamed for rises in childhood obesity and accompanying sedentary behavior patterns (Gordon-Larson & Popkin, 2004; Vandewater, Shim, Capolitz, 2004). Certainly, video games as a pastime are ubiquitous among young people; about 99% of boys and 94% of girls play them (Lenhart, Kahne, Middaugh, Macgill, Evans, & Vitak, 2008). Currently, however, researchers and designers are attempting to harness the motivational power of digital games to help improve players’ physical health (Lu, Kharrazi, Gharghabi, & Thompson, 2013; Oh & Yang, 2010). But evaluations of such games tend to lump them into a single category of “exergames” and examine their overall effectiveness at impacting narrow health indicators (Peng & Liu, 2009; Wylie & Coulton, 2008). Instead, we argue, a more nuanced approach is necessary to evaluate the means and goals of physical activity games, and, perhaps most importantly, to forward a different way of thinking about the agentive role of players in relation to these digital games and to their own health and behavior.

To help address that need, we propose a framework for examining a commercial and research marketplace full of different approaches to the genre of “healthy games,” mostly those emphasizing physical activity. Our framework is driven by the following questions. First, what are different ways of defining effectiveness or outcomes for healthy games? Second, what are the assumptions about learning, engagement, and player agency behind healthy games? And finally, third, how can we use this multi-pronged focus on goals, means, and agency to both evaluate existing healthy games and also design new ones? To address these questions, we review the components of various physical activity gaming technologies to identify the principles of games that are likely to best promote positive health changes over extended periods of time. We examine some currently available commercial and research-based healthy games and discuss how these games can, on the one extreme, create medical or behaviorist “treatments” that position players as the objects of technological intervention, or, alternately, provide fun and engaging ways for players to gain agency and become more aware of their own health data. After articulating the framework and using it to evaluate some other existing games, our paper then describes a game developed by our interdisciplinary research team that combines expertise in the learning and health sciences, is created in collaboration with professional game designers and middle school age school students, and explicitly serves this latter type of agency goal. We provide an overview of a sci-fi exploration game we designed that syncs players’ wearable physical activity monitor data and converts it into “energy” that players can use for game action. Finally, we conclude with an emphasis on the need for game-based systems that can promote authentic engagement and youth agency, such that we are concerned primarily with not only young players’ behavior, but also their insights about the role of physical activity in their everyday lives.  

Background: Obesity, Games, and Technology as a Solution Instead of a Cause

In the U.S. alone, obesity affects two-thirds of the adult population, and chronic diseases are responsible for nearly 70% of deaths (US Department of Health and Human Services, 2012). Metabolic imbalances are largely due to increases in both sedentary lifestyle and consumption of foods high in sugar and low in nutritional value (Keller & Della Torre, 2015). Environments that engender higher consumption of unhealthy foods and low physical activity have been targeted for health and wellness interventions (e.g., Ogden, Carroll, Kit, & Flegal, 2014). Education that enables children to establish lifelong healthy dietary and physical activity patterns in a variety of environments is also crucial.

Advancements in technology have received some of the blame for childhood obesity. Television, computers and videogames are often lumped into a single category called “screen time,” and as such are commonly accused of contributing to low rates of physical activity across the developmental spectrum (see reviews by Gordon-Larson & Popkin, 2004; Rey-Lopez, Rodriguez, Biosca, & Moreno, 2008). Now, however, with the advent of personal health technologies available in the commercial marketplace or integrated into mobile phones, tablets, personal computers, and game systems, this perception of “screen time” as the enemy of fitness is rapidly changing. Some devices capture and provide personal and precisely “quantified” views of health at the level of the individual (Wolf, 2010; Wolf & Kelly, 2010). People can receive objective measures of their personal genome, disease risk, and information on important modifiable lifestyle variables like physical activity, sleep, stress, diet, etc. (Swan, 2013).

Among youth there are numerous technological tools being used to promote health and wellness, most commonly gaming technology and other tools that use gamification principles (Baranowski & Frankel, 2012; Baranowski, Buday, Thompson, Baranowski, 2008; Lenhart et al., 2008). Lu and colleagues (2013) conducted a systematic review that examined the effects of healthy videogames and found them being used increasingly in organized efforts to decrease childhood obesity. Of these 28 healthy videogames reviewed, six were developed by teams of researchers; the remaining 22 were commercially available, most of which used commercial game consoles. Approximately 40% of the studies reviewed actually saw improvement of young players’ anthropomorphic body characteristics such as BMI, percentage of body fat, resting heart rate, etc (Lu, 2013). Overall, these findings challenge the common notion that technology, and particularly gaming technologies, are contributing to youth sedentary patterns.

Goals and Agency: Body and Mind

How sustainable gaming impacts on health are in the long term is not known. In the study by Lu (2013) described in the previous section, short-term improvements in physical indicators such as BMI were found, but other impacts were not evaluated. A medical model of physical improvement is only one way of measuring outcome. Other kinds of positive impact from healthy games might also include changing a player’s awareness of, attitude toward, and sense of agency around explicit exercise or even everyday movement. It is important to point out, however, that these kinds of changes do not reliably occur in a de-personalized general health education context. In a meta-analysis of studies of 1980s-era nutrition education programs, Contento, Manning, and Shannon (1992) demonstrated that while learning general recommendations and concepts could significantly improve learners’ attitudes toward and knowledge of basic nutrition recommendations, these general approaches did not successfully change eating behavior. Focusing on general health knowledge, however, is not the same as building engagement and agency around one’s own health-related life circumstances, something not often specified as a goal of healthy games. An exclusively medical model of impact positions the player as the recipient of games as a therapeutic treatment, such that the player becomes the object of the game’s effect. In contrast, an agency model positions the player as making active choices and strategically thinking about his or her personal health and individual physical activity, either during game play or in everyday life. Nowhere is this distinction more evident than in two very different approaches to technology and health improvement: Stealth Health and The Quantified Self.

“Stealth Health” describes a general strategy that includes but also extends beyond technology design, wherein an intervention or product attempts to sneak healthy practices into daily routines, masking the medical goal of these activities and making them “fun” (Lieberman, 2009). Examples include games designed to encourage large muscle movements and increase heart rate via a jump-on controller players manipulate with their feet, or brightly colored “fruit punch” drinks marketed to children that in fact contain vegetables like carrots and beets. Repeatedly playing these kinds of games or consuming these sorts of foods may cause anthropomorphic or behavioral outcomes to improve, but by design participants remain unaware of why they are changing certain behaviors. In fact, in the most “stealthy” interventions or products, the explicit goal is actually a lack of awareness, since such interventions attempt to actively mask choices individuals would normally select against, such as eating vegetables they usually find unpalatable or doing exercises they typically find unpleasant (Lieberman, 2009). Many health games and apps use stealth health approaches to improve the physical health of players, but the outcomes of such games do not include what Gee (2008) describes as deep learning and learner participation. Some studies suggest that while stealth health games may help prevent childhood obesity, these interventions merely motivate children to change their dietary or physical activity patterns as a result of the game’s goal, not for the intention of enhancing individual health practices, and consequently that the beneficial health outcomes could be described as side effects rather than realized goals (Robinson, 2010a; Robinson, 2010b). Further, individuals who play stealth health games are not better informed to make strategic decisions about their health outside of the game, thus making the players dependent on the games for continued improvement.

In contrast to the lack of awareness and agency described above, “The Quantified Self” movement has as its goal the idea that participants will use objective data to stop engaging in blind or uninformed health-related practices. Quantified Self (QS) is a movement that integrates new mobile and wearable technologies with data acquisition on various aspects of a person’s daily life in terms of day-to-day inputs and performance. (Lee, 2013; Wolf, 2010). QS consumers can purchase sensors or wearable devices to track their personal caloric expenditure, physical activity, sleep patterns, etc., and receive feedback from these devices that can inform how to take better care of their health. In contrast to stealth health approaches that promote users to unconsciously participate in healthy behaviors, QS advocates argue that, via engaging with device data, users become very aware of their behavior, selected health metrics, and consequences of particular practices (Swan, 2013).

Whitson (2013) asserts that part of the reason some individuals find the QS approach successful is that it also operates under the broad umbrella of play. The quantification and surveillance of the self via wearable devices and sensors invites users to see their baseline, set goals, and gain pleasure in reaching those goals. Whitson argues that “when we subject ourselves to this quantification, we come to know and master the self,” (2013, p. 167). QS advocates also assert that access to personal data leads to improved awareness of how personal health metrics are connected to everyday behavioral patterns such as walking, heart rate, food intake, sleep, and so on (Lee, 2013; Wolf, 2010). However, Lee (2013) aptly points out that these self-tracking practices rely on the individual user’s disposition and level of motivation. Furthermore, QS applications ask the user to assess and interpret their data, and future actions are left to the user alone. Interpreting and understanding even those seemingly simplified bar graphs and charts on device-supporting websites or dashboards may confuse and/or bore many youth (Ching & Schaefer, 2014). Consequently, QS tools alone may not be the best way to help children understand their health data or change health-related practices (Schaefer, Ching, Been & German, in press). As Lee (2013) argues, QS needs to be better “situated in meaningful and motivated learning activities” (p. 41). Further, communities with low technology access and low data literacy may experience barriers to self tracking (Ching & Schaefer, 2014; Lupton, 2013; Vahey, Rafanan, Patton, Swan, van’t Hooft, Kratcoski, & Stanford, 2012), and ironically it is often these communities that stand to benefit the most from effective prevention of metabolic disease (Kumanyika & Grier, 2006).

Means to Engagement and Change: Models of Learning, Motivation, and Narrative

While games have the potential to lead to improved health outcomes, it is clearly important to pay attention to the outcomes being measured for effectiveness (i.e., body metrics versus other socio-emotional factors like enjoyment or attitude) as well as the goals of such games for player agency (i.e., awareness or lack thereof). We turn now, however, to the means games use to create player engagement and effect change and describe different ways of thinking about means: models of learning, motivation, and narrative engagement.

One way to examine health-related games is through the lens of learning theory, which can provide insight into the models of learning these games use to encourage healthy changes. On the most basic level, games provide both immediate and distal rewards for particular actions; a correct or desired action yields points or in-game prizes, while an incorrect or unsuccessful action leads to level failure or “Game Over.” As such, basic Behaviorism principles are clearly in play, wherein rewarded actions are more likely to be repeated (Skinner, 1978; Watson, 1925). As a coding framework developed by Adams and colleagues (2009) demonstrates, many movement-based videogames are designed around the idea of rewarding behavior at the micro-level, in terms of immediate in-game reinforcement schedules (Ferster & Skinner, 1957) for isolated physical behaviors such as kicks, jumps, hops, and arm swings, as well as correct clusters or increased intensity or speed of these movements.  Moving away from reinforcement to modeling, Social Cognitive Theory argues that people learn by observing others, and that such observation is similar in learning effect to direct experience (Bandura, 1986). When people observe identical behaviors with differential results, they are more likely to execute those behaviors that are accompanied by positive outcomes or reactions, because these positive observations increase the learner’s sense of efficacy—the expectation that one’s own efforts will yield the desired result. In the context of gaming, the SCT model suggests that actions in a game world where observable outcomes are aligned with prescribed goals, and where players control characters to positive effects (e.g., characters who run long distances get healthier!) are more likely to increase efficacy and thus translate to real-world behavior (Bandura, 2004).

But there is more to learning (or health) than behavior. As humans, we do not just imitate what we see or blindly seek rewards. Our actions are imbued with motivations, meanings, and attitudes, and changing those things is difficult. The Elaboration Likelihood Model (ELM) suggests that, in addition to factors such as attention and behavioral production, motivation is a critical component to learning (Cacioppo & Petty, 1984).  Motivation in particular has long been a challenge to get right for educational games in general (Linehan, Kirman, Lawson, & Chan, 2011), let alone new developments in healthy games. Intrinsic motivation is a desire to do something for enjoyment or for its own sake, whereas extrinsic motivation is a desire to do something because of some outside factor such as material reward, social approval, avoidance of punishment, etc (see review by Ryan & Deci, 2000).  Many learning games have been criticized for relying on extrinsic motivation; for example, solving mathematics problems in order to blow up asteroids, rather than to progress through an interesting and inherently mathematical situation (Habgood & Ainsworth, 2011; Ito, 2008; Kafai, Franke, Author, & Shih, 1998). The same criticism can certainly be leveled at many healthy games, particularly those relying on stealth-health tactics. Changing negative attitudes toward physical activity seems unlikely when the activity is treated like something that has to be concealed in order to be enjoyed.

Regardless of the architecture of learning goals and motivations, some games are just more fun than others. One aspect that contributes to the fun and immersive nature of some kinds of games is a vibrant narrative. Narrative is not often the focus of examining healthy games, from either a health sciences or educational perspective, but story-based games may be a way to engender what Lee (2013) describes as “meaningful and motivated learning activities” involving bodily awareness (p. 41). Narrative theorist Michael Bamberg (2011) argues that, in addition to following the general cycle of rising action to climax, other features such as point of view and identity integration are key to narrative, insofar as stories present a sympathetic protagonist and engage aspects of the self. Specific to healthy games, other scholars have argued for the specific importance of immersive fantasy as a means to engagement, given fantasy’s effectiveness at maintaining player attention and desire for game progress (Baranowksi, Buday, Thompson, & Baranowksi, 2008).

Story-based fantasies are a popular genre for video games in general. Fantasy games create more space for role-playing and interactions with various characters and events than games that adopt nonfiction genres (Parker & Lepper, 1992). Parker and Lepper combined educational content into fantasy-based contexts with a group of third- and fourth- grade students and found that students in the fantasy group were more effectively able to transfer the knowledge from the fantasy context into real-life practice, solving problems more effectively and correctly than students in the non-fantasy group (1992). Yet, as the authors noted, abstract problems masked in the form of a fantasy do not necessarily ensure enhanced learning, as fantasy elements may compete with the educational outcomes. In this sense, even if fantasy story-based activity games enhance a person’s motivation, this motivation could still result in low levels of learning or attitude change. Clearly, fantasy worlds need to be compelling but not so overwhelming as to mask entirely the learning goals of the game.
 

Taxonomy: Mapping Commercial and Research-Based Health Games

In this section we discuss commercial and research-based health games from the perspective of their goals, the degree of agency and awareness they afford players, and how they align with narrative and learning theories. In most cases, we discuss each broad category of healthy games first, followed by a few specific examples of particular games in this category.

Exergames

Exergames are among the most well known types of electronic games that are generally recognized as “healthy.” These digital games use an exertion-based interface to combine exercise with gameplay and encourage people to increase their physical activity while playing the games (Graves, Stratton, Ridgers, & Cable, 2008). In contrast to video games that are usually sedentary and played via manipulating controllers or keyboards with the fingers, exergames require players to jump, walk, and even dance (Yang, Smith & Graham, 2008). Some of the more popular exergames include Nintendo’s Wii Fit (Nintendo, Japan) and Dance Dance Revolution (Konami, Japan). The exergame player uses visual-spatial and hand-eye coordination to effect actions for the character on the screen (see Figure 1).

Game play also requires quick physical reactions to successfully advance in the game, and games often have multiple players compete or cooperate, which creates a virtual and real-time social interaction.

Studies examining the health impact of exergames for children and youth have shown increased caloric expenditure, heart rate and fine motor skills while playing (Adams, Marshall, Dillon, Caparosa, Ramirez, Phillips, Norman, 2009; Staiano & Calvert, 2011). In addition to physical activity, the social and cognitive impacts of exergames may provide additional potential benefits for youth, including increased self-esteem, social interaction, motivation, and attention (Staiano & Calvert, 2011). Yet critics of exergames argue that while these approaches successfully engage children in activities that equate to moderate to intense physical activity, the immediate physical benefits do not necessarily lend themselves to long-term health behavior change (Lyons, Tate, Ward, & Wang, 2009; Oh & Yang, 2010). One of the assumptions behind arcade-based or console-based exergames is that they present a physically active alternative to sedentary gaming. Players, it is argued, will be so motivated to play these games that they will choose to be physically active during a pastime, gaming, where they would not be active otherwise. Yet a study of choices made by children, when they were presented with a combination of active and inactive Nintendo Wii games, demonstrated that children selected inactive games more frequently (Baranowski, et al, 2012). Further, because of the location-constrained aspect of most exergames, players are not encouraged to make strategic decisions about their physical activity patterns outside the game. It comes as no surprise, then, that a research has yet to fully investigate how or whether exergames facilitate deep reflection (Staino & Calvert, 2011).

One of the earliest exergames to achieve widespread commercial popularity is Dance Dance Revolution (DDR) in which players “dance” on a control pad and directions flash on the screen for increasingly elaborate and aerobic placements of their feet (see Figure 2).

Because of its large size, DDR requires a dedicated space and is usually housed in arcades, such that players need to go and play in that location. DDR for the most part is about behavioral replication via attention, repetition, and reinforcement. Players are reminded to pay attention and repeat behaviors through the repeating lights, squares and music (and in fact the action moves so quickly that glancing away from the screen will result in lost cues). Ultimately, players need to retain and produce series of moves over and over again, such that memorization and muscle memory are required. Finally, DDR is a dance-controller game about dancing, rather than the physical activity being in service of some non-active goal, so it satisfies the definition of intrinsic integration. The design of Dance Dance Revolution does not integrate a specific narrative or character point of view; rather, the dancing itself is the point. DDR has yielded results that demonstrate increased physical benefits for cardiorespiratory health in a clinical study (Tan, Chua, & Teh, 2002); however, its immediate benefits must be considered in light of the way the game creates behavioral change in the first place. That is, Dance Dance Revolution promotes players to dance by imitation, but players are never provided with the information to understand the benefits of these imitative dances or how to translate the skills acquired in DDR to other activities.

Play-As-You-Go Games

With the advent of smartphones and tablets that can be carried across contexts and around communities, the location-constrained aspect of many exergames described in the previous section is being overcome by a variety of healthy games in application (or “app”) form. These are games that are designed to direct or accompany agentive movement in and around the real world, encouraging and surrounding activities users might do anyway. Compared to exergames, where the goal is to replace sedentary gaming with exertion-based gaming, many play-as-you-go games are designed to make standard exercise activities more playful. As such, they may enhance motivation for particular physical activities, but the user must make the decision to engage in physical activity, in the context of his or her surrounding environment. This is not to say, however, that all play-as-you-go games encourage meaningful activity, reflection, or integration.

The interactive app Motionmaze can be played on a phone or tablet device, and it engages young children in physical activity, potentially across a variety of locations, but without meaning or intention. Through the lens of a virtual character, players enter a virtual maze and go on a treasure hunt. In order to move the character forward at different speeds, the player must walk, jog, or run—either in place (as directed in Figure 3) or around the room, neighborhood, grocery store, or wherever the player happens to be in the physical world.

The objective is to get the character through the maze quickly and solve problems while staying active. This application encourages children to beat their last time and provides behaviorist positive reinforcement, as the mazes grow in complexity and the rewards get bigger each time the child runs faster. The application uses a lateral movement sensor to detect speed of walking or running, but unfortunately, this feature can be “gamed” by simply shaking the device up and down (also a criticism of Wii exertion-based games—see Marks, Rispen, & Colara, 2015). Further, the game is completely agnostic to the contexts in which users are moving, and it also makes no difference how players move. As such, Motionmaze and other movement-based games like it do not seem to provide meaningful activities for youth to actually learn about their health and the importance of physical activity, they merely attempt to increase the occurrence of physical activity while offering little agency or decision-making to the player.

A play-as-you-go game with narrative fantasy elements designed to accompany meaningful exercise, Zombies, Run! (Erenli, 2012) is a running app that narrates a story of a post-apocalyptic world where zombies are a threat (see Figure 4).

Along with a smartphone sensor that records distance, time and pace, the game proposes missions that accompany the user’s running, like picking up virtual supplies. The runner/user can hear and be chased by zombies, as the audio-accompaniment part of the game is broadcast over the user’s headphones while running. The game does not end once the exercise does, due to a playable app interface that users log in to after their run, and in this interface virtual supplies can be used to help strengthen the user’s base and community to survive zombies in future play. Zombies, Run! does incorporate a narrative, but a predefined story that players listen to while running. The story notifies players to execute the necessary tasks and collect various items. Even though this application records the runner’s distance, speed, and time, research to date has not documented the extent to which this game motivates individuals’ running behaviors (Erenli, 2012). Further, while the game requires player agency, in that users must decide to go running in the first place in order to play the game, its motivational power is potentially troubling. Psychological research demonstrates that intrinsic motivation (in this case, enjoyment of running) can easily be supplanted by extrinsic motivation (in this case, the desire to run so as to accumulate supplies for zombie defense), and that once the novelty of extrinsic motivation wears off, intrinsic motivation may be less likely to return (see Ryan & Deci, 2000).

Another exercise accompaniment game is Super Stretch Yoga (see Figure 5), which integrates storytelling with video examples, music and yoga practices. It is designed for children to find balance and strength in twelve poses featuring cartoons that tell a short story of an animal, followed by a short video for each pose. While advertised to help with issues like childhood obesity and self-esteem, Super Stretch Yoga does not have channels by which players can recognize the yoga poses or reflect on the emotions or physical sensations they bring to the fore. Moreover, the narrative aspect of Super Stretch Yoga is entirely scripted. The child sees and hears a cow “moo,” and mimics the “moo” sound in cow pose. From a narrative theory consideration, as well as a transfer of learning perspective, Super Stretch Yoga could be improved by integrating a more cohesive storyline, so the child would flow from one pose to the next, as if consciously moving through a story in motion. In addition to incorporating more narrative, this approach would also be closer to authentic yoga practice, which typically transitions from one move to the next in meaningful sequences.

Behavior Modeling Games

A category of games that is clearly based in the Social Cognitive Theory of learning is one in which players make in-game decisions that are supposed provide simulated practice for real-world decisions, but in most cases, players are not actually engaging in healthy behavior while gaming. Because of this need for transfer, the goal of behavior modeling games is sometimes educative as well as motivational or imitative. These games are not strictly behaviorist, since the game is not rewarding actual healthy activities on the part of players; however, the game does reward healthy in-game choices, which, for many of these games, are more to the point. Most games that fall into this category are not focused solely on physical activity and attempt to provide more of a comprehensive approach to health improvement by incorporating dietary concerns around food choice and portion size as well.  From an agency perspective, this approach offers a much more substantial role to the informed decisions of the player as an outcome, given that players must make their own food choices in the real world without immediate feedback upon eating. Modern technologies and biological sensors, however, have not advanced to the point where real-time, objective detection of food intake is possible via a device interface. Given the prevalence of stealth-health tactics in attempts to influence children’s food intake in non-gaming interventions, it is an open question whether or not a non-agentive approach would prevail if nutrition sensor technologies were more advanced.

Narratively interesting games seem to be among the most successful in this category, given that simply sorting foods and physical activities into positive and negative choices would no doubt fail to capture children’s attention for very long. Squire’s Quest! (see Figure 6) is situated in medieval times, and players try to get characters like the queen, king, and knights to consume more fruits and vegetables, so they can defend their kingdom and fight off marauding invaders (Baranowski, Baranowski, Cullen, Marsh, Islam, Zakeri, & Honess-Morreale, 2003; Cullen, Zakeri, Pryor, Baranowski, Baranowski, & Watson, 2004). One randomized control trial study implemented SQ with over 1,500 elementary school students demonstrated that participants in the SQ group ate more fruits and vegetables than the control group.

Another narrative-driven and imitative-choice behavior modeling game is Alien Health, in which players feed and exercise an alien character stranded on earth, in order to help him stay healthy and make it home to his own planet (Johnson-Glenberg & Hekler, 2013). This game incorporates both choice-modeling for food intake (see Figure 7) and an exertion-based interface for exercise, as it employs an Xbox Kinect whole-body controller, and players must make the alien do calisthenics using their own bodies.

Health education and knowledge are the goals of this game rather than strictly behavioral outcomes; understanding of current health recommendations and how they translate into everyday choices are the learning goals assessed via pre-post test measures in this research. In fact, the calisthenics required of players are described as being more in service of the learning goals rather than a stealth-health approach (Johnson-Glenberg, 2013).

Tracking and Monitoring Games

Games that employ wearable technologies enable the collection of passive data, such that a user does not have to be consciously interacting with a game interface in order to engage in activities that serve some in-game purpose. Pedometer games are the most common type in this category, and they use the most widely available technology. Some tracking games use dedicated pedometer devices designed just for that game or application, others are apps or web-based games that sync with commercially available pedometers, and still others use the built-in pedometers and/or GPS that come with most newer smartphones. From a learning theory perspective, these games provide behaviorist-style rewards for real-world behavior. In fact one of the arguments behind these games is that they offer immediate feedback and immediate rewards for daily physical activity, whereas the physiological benefits of exercise for health improvement may take weeks or months to be realized and thus fail to adequately motivate individuals to persist in an exercise program. There is typically no SCT observation or simulation that occurs on-screen first in these games, since the user actually has to walk in order to realize game goals or see anything interesting happen on screen. Motivationally, these games are largely not encouraging an intrinsic value for walking or running, as the physical activity is primarily in service of the game goals. Because they are about tracking physical activity throughout a user’s life contexts, they resemble more the Quantified Self approach to user agency than stealth health; however, the extent to which users have access to their own tracking data varies depending on the application.  

At one extreme of this category are games like KidFIT (see Figure 8), which is geared toward young children and employs a wearable activity tracker that syncs to a parent-controlled application that meters out selected rewards. Parents set goals for physical activity, and children can cash in their activity points for prizes of various sorts. This is a strictly behaviorist system with extrinsic motivation rewards, and it also puts decision-making and goal-setting power in the hands of parents rather than young players. There is no fantasy or narrative connected with KidFIT, as the game-like aspect is only insofar as goals are set, achieved, and rewarded. The display on the wearable device itself consists of blinking lights, which could be difficult for children to interpret or connect to their activity patterns, beyond a vague sense of having enough activity or needing more.

This lack of transparency seems incompatible with a Quantified Self emphasis on reflection and interpretation of activity patterns, but since parents set and give out the rewards, children are not necessarily the audience for data yielded by the device anyway.

Fantasy-based games in this category are often themed around caring for or evolving imaginary creatures whose health and development depends on how often and how vigorously they are “taken for walks.” The most narratively rich commercial example we have encountered is the Pokéwalker (see Figure 9), which syncs with the Pokémon videogames Heart Gold and Soul Silver and is incorporated into the fully figured fantasy world of the Pokémon universe.

Any creature that players have unlocked in either videogame can be “transferred” to the Pokéwalker, and that creature then gains experience points from being exercised as the player walks around carrying the pedometer device. From a Quantified Self perspective, how behavior translates into direct metrics of activity is somewhat vague here, as the device displays and transfers only a conversion of pedometer steps into “watts,” which are an indication of the creature’s energy level and experience.

A creature-development game that provides more data and information about physical activity patterns is Wokamon, which runs on smartphones and integrates with either the built-in smartphone pedometer or a host of other Bluetooth commercial activity monitor devices such as Fitbit, Jawbone, etc. While Wokamon provides immediate behaviorist rewards in the form of points, crystals, and unlockable items for creatures such as hats (see Figure 10), it also has a longer timescale for data retention and allows users to look at and reflect on their patterns over previous days or weeks.

So far our aims in this article have been (a) to articulate a framework to examine the goals behind healthy games, the learning models they employ as means to engagement, and the extent to which they provide agency for players to develop insights into their own health practices and make their own decisions accordingly; and (b) to use that framework to analyze a number of existing healthy games across multiple categories. Of course all healthy games have as their goal the improvement of health in some way, but games employ a variety of means toward those ends and may look fairly different when considered from the perspective of the framework we outline. Table 1 demonstrates how healthy games can be categorized according to their means for engagement and the goals for desired impact.

 

In the left column of Table 1 are those games that are based on a micro-level behavioral reinforcement model, wherein individual movements and intensity are rewarded within the game immediately after they are performed (Adams, et al, 2009). These games are also all exergames, in that they are designed to encourage and reward physical activity taking place during the immediate experience of game play, at the game console or with app-in-hand. In the middle column we have games that are related to a Quantified Self model of engagement (Wolf, 2011; Whitson, 2013), in that they all involve portable devices or sensors that players carry with them into the contexts of their everyday lives, walking or running around their communities. With the exception of KidFIT, most of these are also all games designed to accompany physical activity, in that there is a responsive game element during the players’ exercise (such as the sound of zombies while the player is running, or the Wokamon monster becoming happier over the course of a walk). Finally, the right-hand column contains games whose primary mode of engagement is immersion in rich fantasy and narrative-driving action (e.g., Baranowski et al, 2008), where the player also manipulates in-game characters who model behavioral choices and the player can see consequences for health-related actions (Bandura, 2004). For the most part, these are also games whose goal is impacting the player’s behavior in the physical world outside the game, after the game is played—food choices, other kinds of exercise, etc. In addition to the sorting of games into these dual categories, the table also indicates relative position of games within each one and potential overlaps; for example, Motionmaze also includes a basic motion sensor, and Zombies, Run! and Pokéwalker are also connected to other parts of their games that focus on a fantasy narrative.

Categorizing these games can lead to some realizations about how models for learning, behavior change, and modes of engagement are related. Games such as Alien Health, Zombies, Run!, and Squire’s Quest! are designed by health researchers who have written articles about their design and effectiveness, so those are somewhat easier to classify. But without the insights of the designers, some of these categorizations are based on analyses of the functional effects of the games, rather than their explicit intents. Further, our use of the term “Quantified Self” for the middle column of games is based on the presence of a physical sensor and the incorporation of ambulatory physical activity; however, these games do not include the important QS goal of encouraging insight and reflection into users’ typical activity patterns (Wolf, 2010). As a way of illustrating what a game might look like that attempts to incorporate more of the Quantified Self model, as well as making visible the goals-means-agency intentions behind such a game, in the next section we describe our own game design efforts toward these ends. Note that we are not presenting our own game as some kind of paragon, but rather as an example, both promising and flawed (as most designs are).

Terra: Integrating Narrative, Motivation, and Quantified Self

When we set out to make our own healthy game for tweens and teens, we had several goals in mind. We wanted to include as much of the Quantified Self approach to user agency and data reflection as possible. This meant that our approach would involve youth getting feedback not on some artificial kind of activity we added to their environment but on the role of physical activity in their everyday lives. As such, we wanted to design for the wearable technology tracking/monitoring genre, but we needed a device that would actually give full access to real health metric data. So we developed a game that would work with an already commercially available physical activity monitor. We use Fitbit devices, because they are based on an open-source API that can be accessed for programming third-party applications, they have an entry-level device that is under $50 and is inexpensive for providing to youth in schools and after-school programs in our research studies, and the device has an active display so the wearer can glance down at any moment during the day for immediate feedback (see Figure 11).

We wanted multiple ways for youth to interact with and reflect on their data, so we not only relied on the real-time feedback from the devices themselves and their accompanying dashboard on the Fitbit website, we also built multiple in-game representations of physical activity over daily, weekly, and longer timeframes. Further, the outcomes we designed for were not based on a medical model of impact. Certainly we hoped that youth would engage in more physical activity as a result of wearing their devices and playing our game, but beyond that, we wanted them to gain some insights about how active they were and what might account for those patterns. Research has shown the crucial role that social support structures, physical and material environments, institutions and ecologies play in potentially helping facilitate sustained health behavior changes (Golden & Earp, 2012), and we wanted youth to consider these factors in their reflections. As a result, much of our research study so far has used methods like focus groups, observations, and interviews with youth to talk with them about their thinking, in addition to body metrics and analysis of the device data streams to determine impact on physical activity (Ching & Schaefer, 2014; Schaefer, Ching, Breen & German, 2016). Because we were working with schools and after-school programs, where resources are scarce and buying additional dedicated technologies like gaming consoles is not possible (and where many portable student devices such as smartphones are restricted anyway), we built a game that is web-based and playable on any browser from computers at school, home, the library, etc.

Finally, and arguably most importantly, we wanted our game to have a rich, compelling narrative and be fun to play. Rather than assuming we knew what youth would want, we collaborated with professional game designers and started by working with youth in focus groups to determine a storyline and narrative world they found exciting, what art styles appealed to them, and what game mechanics and dynamics were most enjoyable and easy to follow. At the end of nearly a year of exploration, we came up with Terra.  Players of Terra are space explorers who have landed on a desolate planet. They set up individual domed bases, with the goal of completely “terraforming” the planet so that more of their people can come live there. Terra is accessible via most online web browsers (given the appropriate permissions and login) and downloads information from the Fitbit online database each time a player logs in. The game displays an “Energy” window that details how many game moves are possible each game day based on in-game metrics and steps. For example, for each 1,000 steps a player has taken the previous “real-world” day, they get one extra move in the game that day (see Figure 12).

Players can use their energy moves in a number of ways, including acquiring alien creatures and caring for them, growing crops, exploring and expanding the boundaries of their terraformed area, constructing buildings and other infrastructures, or amassing resources to prepare for planetary weather or other disasters. As such, this game invites players to be more aware of their physical activity patterns and can motivate players to increase their step count, in an attempt to acquire more energy to terraform their planets. The game employs 2-D graphics and 3-D isometrics to give an artistic and ancient look to the game elements, while also providing a deep and exploratory feel to the navigation and action.

By integrating sound, art, and animation, Terra invites players to visually and narratively immerse themselves into the game world (Bamberg, 2011). While deciding the best way to terraform their planets, players also have access to an on-screen dashboard that summarizes their game statistics (planetary days, ore stores, food resources, energy, atmos). This helps youth in making strategic decisions about how to best use their energy. As the game progresses, the landscape of the world that players create becomes an aggregate visual representation of their synced activity over the variable time frame of the game campaign, with each player’s landscape reflecting not only strategic in-game decisions but also the extent of their daily fitness (see Figure 13). As such, Terra attempts to facilitate an understanding of how physical activity is made relevant to the player’s playing, terraforming, and ultimately, their telling of how the story will end.

To learn about how youth perceived Terra and interacted with their Fitbit devices, several focus group and individual interviews were conducted with middle school youth. Using a grounded theory approach (Martin & Turner, 1986), transcripts were analyzed by generating a list of themes and then developing a list of open codes. We met and discussed the subcategories that fell under each theme and then coded the transcripts using those categories. One theme that arose during the individual interviews that relates to motivation theory is the notion that youth liked the fact that their game play was connected to their actions outside the game world. In this quote from an individual interview, one of our researchers asked the participant if she liked the game, and the participant responded:

“It’s fun. … it’s different compared to the other games I play….uh, because it depends on really, like, what you do every day and how many steps you take. Usually most other games are just, like, it doesn’t really involve with your daily life.”

What is interesting about this excerpt is that our participant is aware that Terra, unlike “other games,” can be actually integrated into and involved with her “daily life.” She recognizes the inter-relationships among her Fitbit device, the steps she takes throughout her daily activities, and the quality of her gaming experience.

After being engaged in this research for several years now, we realize that having a strong ecological understanding is essential to supporting sustainable health behavior change for youth. A quantitative-only look at the youth step count device data from the first year of our study suggests that there was a strong initial effect of wearing Fitbits, but that this effect then shrank. However, during our focus groups and individual interviews with youth, we discovered that they made changes to their activities initially that spiked their step count (such as repeatedly running in place) but were ultimately unsustainable. Eventually, however, some students figured out how to make sustainable changes such as participating more in Physical Education class at school, even in contexts where the built environment of their neighborhoods did not offer many opportunities for recreational exercise (Ching & Schaefer, 2014; Scafer, Ching, Breen & German, 2016). We would not have gained this insight if we had focused only on the quantitative data; thus it is critical to examine not just quantitative outcomes but also the meanings and practices behind these numerical findings. This approach extends beyond a strictly medical, individual model of behavior and looks at contexts and communities through an ecological lens (Stewart, Hagood & Ching, 2015).

Conclusions

In the ever-expanding landscape of healthy games, there are games that seek to make sedentary gaming more active, games that accompany physical activity and seek to make it more fun, games that model healthy choices and hope those choices transfer to everyday life, games that persuade players to change their attitudes toward health and nutrition, and games that motivate players to be more active every day via tracking and monitoring. There are relatively few games, however, that aim to impact player insight and reflection—helping to increase players’ awareness of their own physical activity patterns, helping them represent and reflect on the role of physical activity in their everyday lives, and encouraging them to increase their physical activity in a sustainable way. Although most healthy games themselves are not explicitly designed with insight and reflection goals in mind, it is also noteworthy that, with few exceptions, the vast majority of research on the effectiveness of healthy games also does not include participant perspectives, as if the bodies involved in these studies are separate from the minds that inhabit them. Further, a medical model focusing solely on changes in body metrics or raw increases in physical activity as the only desirable outcomes to be measured frames whatever participant baselines may be as problems in need of fixing. Such an approach does not offer agency or intentionality to the players of these games, nor does it consider that learning to pay attention to physical movement, rather than concealing it behind a stealth-health disguise, may be critical to long-term changes in basic orientation to health.

Certainly we are not arguing that Terra is somehow the ideal of healthy games. We acknowledge that the problem of intrinsic versus extrinsic motivation that plagues the vast majority of gamification attempts in education and health is also problematic in our design. When we hear from youth participants that they want to go out and walk more, or participate more in PE, or “be less lazy” because of their desire to make progress in Terra, we worry that they are not learning to value physical activity for its own sake, or that we might possibly be supplanting intrinsic motivation for already active players. But, based on our initial findings, there is clearly something that deserves more attention and study about a rich narrative in a detailed fantasy world that is nevertheless strongly grounded in real data from players’ everyday practices. We see youth being empowered and feeling satisfied with changes they have made to their physical activity patterns, not because they were somehow tricked into moving more, but because they had the information, the motivation, and the agency to make those changes themselves. Moving forward, we will continue to study how youth can be aware of and engage playfully with their own health data, and we will continue to forward technology designs that put player agency, learning, and narrative at the center. We hope that the goals-means-agency framework for examining and designing healthy games articulated in this article will help other researchers and designers with similar aims.

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References

Adams, M.A., Marshall, S.J., Dillon, L., Caparosa, S., Ramirez, E., Phillips, J., Norman, G.J. (2009). A theory-based framework framework for evaluating exergames as persuasive technology. Proceedings of the 4th Annual International Conference on Persuasive Technology. (p. 45-53) Association for Computing Machinery.

Bamberg, M. (2011). Narrative practice and identity navigation. In J.A. Holstein & J.F. Gubrium (Eds.), Varieties of narrative analysis (pp. 99-124). London: Sage Publications.

Bandura A. (1986). Social foundations of thought and action: A social cognitive theory.  Englewood Cliffs, NJ: Prentice Hall.

Bandura, A. (2004). Health promotion by social cognitive means. Health Education & Behavior, 31(2), 143-164.

Baranowski, T., Abdelsamad, D., Baranowski, J., O’Connor, T. M., Thompson, D., Barnett, A., Cerin, E., & Chen, T. A. (2012). Impact of an active video game on healthy children’s physical activity. Pediatrics, 129(3), 636-642.

Baranowski, T., Baranowski, J., Cullen, K. W., Marsh, T., Islam, N., Zakeri, I., & Honess-Morreale, L. (2003). Squire’s Quest!: Dietary outcome evaluation of a multimedia game. American Journal of Preventive Medicine, 24(1), 52-61.

Baranowski, T., Buday, R., Thompson, D., Baranowski, J. (2008). Playing for real: Video games and stories for health-related behavior change, American Journal of Preventive Medicine, 34, 1, 74-82.

Baranowski, T. (2013). Games and childhood obesity. Games for Health Journal, 2(3): 113-115.

Baranowski, T., & Frankel, L. (2012). Let’s get technical! Gaming and technology for weight control and health promotion in children. Childhood Obesity (Formerly Obesity and Weight Management), 8(1), 34-37.

Cacioppo, J. T., & Petty, R. E. (1984). The elaboration likelihood model of persuasion. Advances in Consumer Research, 11(1), 673-675.

Ching, C. C., Schaefer, S. (2014). Identities in motion, identities at rest: Engaging bodies and minds in the design of fitness gaming for youth. In V. R. Lee (Ed), Learning technologies and the body: Integration and implementation in formal and informal learning environments. New York: Routledge.

Contento, I. R., Manning, A. D., & Shannon, B. (1992). Research perspective on school-based nutrition education. Journal of Nutrition Education, 24(5), 247-260.

Cullen, K. W., Zakeri, I., Pryor, E. W., Baranowski, T., Baranowski, J., & Watson, K. (2004). Goal setting is differentially related to change in fruit, juice, and vegetable consumption among fourth-grade children. Health Education & Behavior, 31(2), 258-269.

Gee, James Paul (2008). Learning and games. The ecology of games: Connecting youth, games, and learning. In Salen, K. (Ed.), The John D. and Catherine T. MacArthur Foundation Series on Digital Media and Learning. Cambridge, MA: The MIT Press.

Erenli, K. (2012, September). The impact of gamification: A recommendation of scenarios for education. In Interactive Collaborative Learning (ICL), 2012 15th International Conference on (pp. 1-8). IEEE.

Ferster, C.B. & Skinner, B.F. (1957). Schedules of reinforcement. New York: Appleton-Century-Crofts.

Golden, S.D, & Earp, J.A. (2012). Social ecological approaches to individuals and their contexts twenty years of Health Education & Behavior, 39(3): 364-372.

Gordon-Larson, P. & Popkin, BM. (2004). The nutrition transition: Worldwide obesity dynamics and their determinants. International Journal of Obesity, 28, S2-S9.

Graves L, Stratton G, Ridgers ND, Cable NT. (2007). Comparison of energy expenditure in adolescents when playing new generation and sedentary computer games: cross sectional study. BMJ : British Medical Journal. 335(7633):1282-1284.

Habgood, M. J., & Ainsworth, S. E. (2011). Motivating children to learn effectively: Exploring the value of intrinsic integration in educational games. The Journal of the Learning Sciences, 20(2), 169-206.

Ito, M. (2008). Education vs. entertainment: A cultural history of children’s software. The ecology of games: Connecting youth, games, and learning, 89-116. MIT Press.

Johnson-Glenberg, M. C. (2013). Using Motion Sensing for Learning: A Serious Nutrition Game. In Virtual, augmented and mixed reality. Systems and applications (pp. 380-389). Springer Berlin Heidelberg.

Johnson-Glenberg, M. C., & Hekler, E. B. (2013). ” Alien health game”: An embodied exergame to instruct in nutrition and MyPlate. Games for Health: Research, Development, and Clinical Applications, 2(6), 354-361.

Kafai, Y. B., Franke, M. L., Ching, C.C., & Shih, J. C. (1998). Game design as an interactive learning environment for fostering students’ and teachers’ mathematical inquiry. International Journal of Computers for Mathematical Learning, 3(2), 149-184.

Keller, A. & Della Torre, S. B. (2015) Sugar-sweetened beverages and obesity among children and adolescents: A review of systematic literature reviews. Childhood Obesity, 11, 338-346.

Kumanyika, S. K., & Grier, S. (2006). Targeting interventions for ethnic minority and low-income populations. The Future of Children, 16(1), 187-207.

Lee, V. R. (2013). The quantified self (QS) movement and some emerging opportunities for the educational technology field. Educational Technology, 39-42.

Lenhart, A., Kahne, JK., Middaugh, E., Macgill, AR, Evans, C., & Vitak, J. (2008). Teens’ gaming experiences are diverse and include significant social interaction and civic engagement. Pew/Internet: Pew Internet & American Life Project, 1-64.

Lieberman, D. A. (2009). Designing serious games for learning and health in informal and formal settings. Serious games: Mechanisms and Effects, 117-130.

Linehan, C., Kirman, B., Lawson, S., & Chan, G. (2011, May). Practical, appropriate, empirically-validated guidelines for designing educational games. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1979-1988). ACM.

Lu, A. S., Kharrazi, H., Gharghabi, F., & Thompson, D. (2013). A systematic review of health videogames on childhood obesity prevention and intervention. Games for Health Journal, 2(3): 131-141.

Lupton D. (2013). Quantifying the body: monitoring and measuring health in the age of mHealth technologies, Critical Public Health, 23(4): 393-404.

Lyons, EJ, Tate, DF, Ward, DS, Wang, X. (2009). Energy intake and expenditure during sedentary screen time and motion-controlled video gaming. The American Journal of Clinical Nutrition, 2(96): 234-239.

Marks, D. W., Rispen, L., & Calara, G. (2015). Greater Physiological Responses While Playing XBox Kinect Compared to Nintendo Wii. International Journal of Exercise Science, 8(2), 7.

Martin P.Y., Turner B.A. (1986). Grounded theory and organizational research. The Journal of Applied Behavioral Science, 22, 2.

Ogden CL, Carroll MD, Kit BK, Flegal KM. (2014). Prevalence of childhood and adult obesity in the United States. JAMA, 311(8):806-814.

Oh, Y., & Yang, S. (2010). Defining exergaming and exergames. Proceedings of the Meaningful Play Conference. Michigan State University.

Parker, L. E., & Lepper, M. R. (1992). Effects of fantasy contexts on children’s learning and motivation: making learning more fun. Journal of personality and social psychology, 62(4), 625.

Peng, W., & Liu, M. (2008). An overview of using electronic games for health purposes. Handbook of Research on Effective Electronic Gaming in Education, pp. 388-401. New York: Information Science Reference.

Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion (pp. 1-24). Springer New York.

Przybylski, A. K., Rigby, C. S., & Ryan, R. M. (2010). A motivational model of video game engagement. Review of General Psychology, 14(2), 154.

Rey-Lopez, J., Rodriguez, G., Biosca, M., Moreno, L. (2008). Sedentary behaviour and obesity development in children and adolescents. Nutrition, Metabolism & Cardiovascular Diseases, 18, 242-251.

Robinson, T. N. (2010a). Stealth interventions for obesity prevention and control: Motivating behavior change. Obesity Prevention: The Role of Brain and Society on Individual Behavior, 319-327.

Robinson, T. N. (2010b). Save the world, prevent obesity: piggybacking on existing social and ideological movements. Obesity, 18(S1), S17-S22.

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67.

Salen, K., Gresalfi, M., Peppler, K., & Santo, R. (2014). Gaming the system: Designing with Gamestar Mechanic. MIT Press: Cambridge, MA.

Schaefer, S. E., Ching, C. C., Breen, H., German, J.B. (2016). Wearing, thinking, and moving: Testing the feasibility of fitness tracking with urban youth. American Journal of Health Education, 47 (2016), 1.

Skinner, B. F. (1978). Reflections on behaviorism and society. Prentice Hall.

Southard, D. R., & Southard, B. H. (2006). Promoting physical activity in children with MetaKenkoh. Clinical and Investigative Medicine, 29(5), 293.

Staiano, A.E., & Calvert, S. L. (2011). Exergames for physical education courses: Physical, social, and cognitive benefits. Child Development Perspective, 5(2): 93-98.

Stewart, M., Hagood D., Ching C. (2015). A tale of two schools: Terrain and resources in virtual games and physical communities. In Oschner, A. & Steinkuhler, C. (Eds), Proceedings of Games+Learning+Society, 2015. ETC Press.

Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85-99.

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.

Thompson, D., Baranowski, T., Buday, R., Baranowski, J., Thompson, V., Jago, R., & Griffith, M. J. (2008). Serious video games for health: how behavioral science guided the design of a game on diabetes and obesity. Simulation & Gaming, 41(4): 587–606.

US Department of Health and Human Services. (2012). Healthy People 2020. Washington, DC: USDHHS; 2012.

Vahey, P., Rafanan, K., Patton, C., Swan, K., van’t Hooft, M., Kratcoski, A., & Stanford, T. (2012). A cross-disciplinary approach to teaching data literacy and proportionality. Educational Studies in Mathematics, 81(2), 179-205.

Vandewater, EA, Shim, M., Capolitz, AG. (2004). Linking obesity and activity level with children’s television and video game use. Journal of Adolescence, 27, 71–85

Watson, J. B. (1925). Behaviorism. Transaction Publishers.

Wolf, G. (2010). The data-driven life. The New York Times, 28, 2010.

Wolf, G., Carmichael, A., & Kelly, K. (2010). The quantified self. TED http://www. ted. com/talks/gary_wolf_the_quantified_self. html.

Whitson, J.R. (2013) Gaming the quantified self. Surveillance and Society, 11(1/2): 163-176.

Wylie, CG, & Coulton, P. (2008). Mobile exergaming. Paper presented at the 2008 International Conference on Advances in Computer Entertainment Technology. Abstract retrieved from Advances in Computer Entertainment Technology.

Yang, S., Smith, B, & Graham, G. (2008) Healthy video gaming: Oxymoron or possibility? Innovate: Journal of Online Education, 4(4): 1-6.

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Biographies

Cynthia Carter Ching is an Associate Professor of Education at the University of California Davis, where she conducts research at the intersection of technology, learning, identity, and embodiment. Her work examines how people represent and negotiate aspects of themselves via technology in classrooms, in online environments, and in games. Currently she heads a project funded by the National Science Foundation to investigate connections among wearable fitness devices and online gaming for underserved youth. Her work has appeared in Computers & Education, Teachers College Record, American Journal of Health Education, and Journal of the Learning Sciences.

A Ph.D. Student in Education at UC Davis, Roxanne Rashedi is interested in emotions, the body, and movement-based contemplative practices. Currently she works as a Graduate Student Researcher at UC Davis and Graduate Research Assistant at the MIND Institute. In addition to participating in Dr. Ching’s work on wearable technology, she is piloting a school-based yoga program to examine its feasibility and acceptability among teachers, students, and parents. Beyond her research activities, Roxanne also examines the literacy practices of yoga instructors and the ways in which teachers’ stories showcases their lived experiences and the connections they experience between their practice and writing.

Sara Elizabeth Schaefer is the Associate Director of Children’s Health & Education Programs at the Foods for Health Institute. She has a Ph.D. is in Nutritional Biology from UC Davis. Her research and teaching focuses on interdisciplinary, translational and participatory efforts that engage children in managing their individual health and diets. She has a special interest in emerging technologies, virtual gaming and other interactive media tools that traverse socioeconomic, cultural and gender barriers to inspire children to be their “own health clinicians.” Her work infuses health and science curricula with Quantified Self -inspired health tracking, and creates innovative ways of delivering personalized, actionable health feedback to young people. 

 

© 2015 Cynthia Carter Ching, Roxanne Rashedi and Sara Elizabeth Schaefer, used by permission

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Technoculture Volume 5 (2015)