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Health Behavior Theory in Physical Activity Game Apps: A Content Analysis

Health Behavior Theory in Physical Activity Game Apps: A Content Analysis Background: Physical activity games developed for a mobile phone platform are becoming increasingly popular, yet little is known about their content or inclusion of health behavior theory (HBT). Objective: The objective of our study was to quantify elements of HBT in physical activity games developed for mobile phones and to assess the relationship between theoretical constructs and various app features. Methods: We conducted an analysis of exercise and physical activity game apps in the Apple App Store in the fall of 2014. A total of 52 apps were identified and rated for inclusion of health behavior theoretical constructs using an established theory-based rubric. Each app was coded for 100 theoretical items, containing 5 questions for 20 different constructs. Possible total theory scores ranged from 0 to 100. Descriptive statistics and Spearman correlations were used to describe the HBT score and association with selected app features, respectively. Results: The average HBT score in the sample was 14.98 out of 100. One outlier, SuperBetter, scored higher than the other apps with a score of 76. Goal setting, self-monitoring, and self-reward were the most-reported constructs found in the sample. There was no association between either app price and theory score (P=.5074), or number of gamification elements and theory score (P=.5010). However, Superbetter, with the highest HBT score, was also the most expensive app. Conclusions: There are few content analyses of serious games for health, but a comparison between these findings and previous content analyses of non-game health apps indicates that physical activity mobile phone games demonstrate higher levels of behavior theory. The most common theoretical constructs found in this sample are known to be efficacious elements in physical activity interventions. It is unclear, however, whether app designers consciously design physical activity mobile phone games with specific constructs in mind; it may be that games lend themselves well to inclusion of theory and any constructs found in significant levels are coincidental. Health games developed for mobile phones could be potentially used in health interventions, but collaboration between app designers and behavioral specialists is crucial. Additionally, further research is needed to better characterize mobile phone health games and the relative importance of educational elements versus gamification elements in long-term behavior change. (JMIR Serious Games 2015;3(2):e4) doi: 10.2196/games.4187 KEYWORDS health and fitness apps; mobile phone; behavioral health; theory; content analysis; physical activity http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 1 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al contained few evidence-based practices, and Cowan et al [28] Introduction reported in a content analysis of physical activity apps that the sample contained low levels of HBT, suggesting that the lack Serious games, or games whose primary purpose is to educate of behavioral components may have been due to the widely rather than entertain [1], have become a popular research focus varying professional backgrounds of app developers. because of their potential application in fields such as education, Conversely, in a content analysis of physical activity video military, business, and health and wellness [2]. Games appear games, Lyons et al [33] reported that the games contained a to be an emerging option for behavioral change, especially relatively high percentage of health behavior constructs [33]. health behaviors, as serious games address innate psychological It may be that serious health games in general contain high needs while offering intrinsic motivation in the form of fun [3]. amounts of HBT, whether HBT is consciously included or Serious games may also have potential to impact health behavior because games by design are more conducive to inclusion of change on a widespread level because of their appeal and the HBT, though there has not been enough research conducted to popularity of gaming. Furthermore, 59% of Americans play determine whether this is true. video games, and the average household owns at least one game console, PC, or mobile phone [4]. Serious games have been As health professionals are increasingly using mobile phone increasingly utilized in public health interventions [5], and many apps in interventions to increase physical activity, research on have shown promise in changing behavior in areas such as the content of such apps is important. Although many content tobacco cessation, violence prevention, and mental health [6-8]. analyses for health and fitness apps have been recently conducted [26-31] and analyses of exergames are emerging Serious games for public health have typically been developed [33], currently, no studies have been conducted to investigate as video games [9,10]. Exergames, or video games that require HBT in serious games developed for mobile phones. The physical movement in order to play, are a particularly popular purpose of our study was to identify the currently available most tool for health professionals especially as physical activity popular physical activity health games developed for mobile among the US population has decreased and chronic diseases phones and to conduct a content analysis of HBT in these games. such as obesity have increased [11-13]. While serious games were initially designed for personal computers and more recently Methods for gaming systems, mobile phones are another increasingly viable platform for health and physical fitness games for several Study Design reasons. First, mobile phones are widely used; mobile phone Our study was a content analysis of HBT contained in physical use increased 22% over the year 2013 alone, and among US activity game apps selected from among the apps available in households that own a device to play video games, 53% play the iTunes App Store’s Health and Fitness category. Two games on a mobile phone [4]. Second, game-like elements are graduate students trained in HBT coded the apps. already frequently utilized by health app developers. Lister et al found that elements of gamification, or the “use of game Sample Identification design elements in non-game contexts” [14], appeared in a large The sample was collected from the Apple App Store in the fall percentage of health and fitness apps [15]. Third, the use of of 2014. Apps designed for iPhone use were chosen, because apps in health interventions is already prevalent among public many similar app content analyses have used Apple’s App store health professionals [16-18], and interventions using serious for sample selection [27,28,30,31]. This sample contained apps health games on mobile phones are emerging as well [19-21]. categorized under the health and fitness section of the App Store The few health behavior change interventions that have utilized and were related to physical activity. Physical activity mobile serious games developed for a mobile phone platform have phone games were selected for two reasons: (1) physical activity shown to improve health outcomes in areas such as diabetes is both an impactful and neglected health behavior [12,13], and management and healthy eating [19-21]. (2) interventions utilizing physical activity apps are a growing Much research suggests that health interventions designed area of interest for health researchers [34-37]. There were 42 around health behavior theory (HBT) are more effective in key search terms that were established prior to the sample changing behavior than those which are not [22-25]. Many collection, using key phrases for both physical activity and content analyses of health apps indicate that such apps generally games. Keywords included fitness terms such as “running”, contain low levels of HBT or are not adequately designed for “walking”, “workout”, “exercise”, and others related to these long-term behavior change [26-31]. For example, Breton et al behaviors, as well as game keywords, including “challenge”, [32] noted in a content analysis of weight-loss apps that most “adventure”, and “interactive” (Table 1). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 2 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 1. Search terms. Physical activity terms Gamification terms Dance Game Exercise Avatar Fitness Reality game Run Virtual Fit Challenge Team Race Train Quest Trainer Adventure Goal Interactive Walk Simulator Track Augmented reality Tracker Running Trek Workout Health Cycling Aerobics Cardio Weight training We have formal training in public health and health behavior Coding Procedure and adapted the search terms from a previous content analysis Each app selected for final inclusion was coded into an initial of health theory in fitness apps [28]. Search terms were entered sampling rubric using Qualtrics online survey software. The into the Apple App Store on iPads, as iPads allow filtering of coders downloaded each app to an iPad or iPhone and played results. Search results were narrowed by (1) iPhone only, (2) each game for a minimum of 30 minutes or until completing health and fitness, and (3) popularity. Previous content analyses one level to increase familiarity with the user interface and of apps ordered search results by popularity to ensure that the available functions. The coders then used a theory-based apps that were reviewed were highly used [15,28]. instrument to conduct the content analysis for each app. The first 500 most popular apps were chosen for each search Measurement term, as the app store does not sort by page number. The instrument and methodology used for coding was adapted Additionally, as adapted from Lister et al [15], searching through from an instrument used by Cowan et al [28] designed to assess a set number of primary results is enough for an adequate theoretical content of physical activity apps. A similar rubric sample, because users do not typically search beyond the first was used, with the addition of more questions about social few search pages [38,39]. networking sites utilized in the apps, expanding the options for The detailed written descriptions for the first 500 apps that type of exercise utilized in the app, and tailoring the items for appeared in the search results under each topic were analyzed a serious game setting. to assess whether each app met the criteria for a serious health Each app was coded using a rubric with 100 theoretical items, game. The definition for serious game was taken from containing five questions each for 20 different constructs, as definitions provided by Michael and Chen [1] and Shegog [19] used by Cowan et al [28]. The coding rubric required choosing and required that the app was primarily intended to educate, 0 points when the construct was not present in the app, 1 point rather than entertain, as well as change a health behavior; for generalized information on the construct, 2 points for additionally, each app needed to either (1) contain a fantasy assessing user’s knowledge relating to the construct, 3 points storyline or narrative, or (2) include the possibility of failure. for providing feedback about user’s knowledge on the construct, The initial search revealed 86 apps that were originally selected 4 points for general assistance relating to the construct, and 5 as meeting the criteria. After reviewing all of the apps, 52 were points for individualized assistance to improve relative to the identified for final inclusion. Apps were excluded that required construct. The points for each construct were added together special equipment (e.g., bikes, treadmills, pedometers, heart for each app. This resulted in a HBT score ranging from 0 to rate meters, GPS) (8), could not be located in the App Store upon subsequent searches (5), failed to operate (8), or upon We also coded for gamification elements. The specific further investigation did not meet the criteria for a physical gamification elements coded for were selected from an activity game (13). instrument used by Lister et al [15] and from the definition adapted from Michael and Chen [1] and Shegog [19] (Table 6). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 3 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al determine whether there was an association between HBT and Analysis price, as well as HBT and total number of gamification elements. Coded data were imported from Qualtrics and analyzed using SAS Studio. To verify the level of interrater reliability, both Results coders independently coded 10 common apps, approximately 12% (10/86) of the original sample and 19% (10/52) of those Sample Characteristics retained for final inclusion. A Cohen’s kappa coefficient, a Characteristics of the sample are shown in Table 2.The mean method commonly used in content analysis research, was HBT score was 14.98 out of 100 points. One of the apps, calculated to measure interrater agreement (κ=.60) with 97% SuperBetter, was an outlier with a much higher theory score agreement [15,28]. This is categorized as high-moderate than the rest of the sample (HBT score of 76 out of 100). Four agreement, which ranges from .41 to.60 and is an acceptable of the apps (GPS Invaders, MotionMaze Holiday Adventure, level of interrater agreement [40]. Descriptive statistics were Mapventures, and TrezrHunt Free) contained no HBT elements used to report on the integration of HBT into physical activity as dictated by the coding rubric. Walking (56%, 29/50) and mobile phone games. A Spearman correlation was used to running (42%, 22/50) were the most common exercises incorporated into apps (Table 3). Table 2. App characteristics. App name HBT score App name HBT score SuperBetter 76 Rare Candy—Epic Habit and Goa 12 Yoga Retreat 37 Rare candy free 12 Zombies, Run! 5k Training 35 Wokamon 12 iBelly Workout 29 Silk Road Walk 12 The Walk 29 Runno 11 Workout in a Bag—for kids 29 Box the Bag 9 Yes, Drill Sergeant! 28 Block Sports 9 RunAlice 28 Walky 8 Walk it! 24 AR Basketball 8 Zombies Run! 24 Battlesuit Runner Fitness 8 Ninja Fitness Free 24 Jump Boy 8 Streetquest—run a game 23 iBowl 8 Walk n' Play 22 MotionMaze Trick or Treat 7 Burn Your Fat with Me! 21 Hike the World—GPS Tracker 6 PushUp Club Free 20 MotionMaze 6 NFL Play 60 19 Paranoid 5 Habit Monster 17 treasure island GPS, 5 Turfly 17 AR Soccer 4 Daily Spartan 17 Keep Moving 4 Walkr—Galaxy Adventure in You 16 Pygmalions Challenge 1 FitQuest Lite 16 GPS Fun Lite 1 RunZombieRun 16 Gigaputt 1 7 Min Workout Zombie Survival 15 GPS Invaders 0 HuntedApp 14 MotionMaze Holiday Adventure 0 TapCloud 13 Mapventures 0 Superhero Workout 13 TrezrHunt Free 0 http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 4 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 3. Exercise type in apps. Forms of exercise n % Walking 29 56 Running 22 42 None/general movement 17 33 Weight lifting/bodyweight exercises 13 25 Other 9 17 Stretching 8 15 Jumping 5 10 (0-100). Goal setting, self-monitoring, and self-reward were the Presence of Specific HBT Constructs most-reported constructs found. Only self-monitoring and Table 4 shows the mean score (0-5) for the presence of HBT goal-setting had a median score greater than zero. For both, the constructs measured in the sample, as well as the overall score median score was 5. Table 4. HBT score by construct (N=52). HBT n (%) Median Mean SD Overall score 52 (100) 12.5 14.98 12.92 Capacity General information 20 (38) 0 1.48 1.99 Self-monitoring 30 (58) 4 2.25 1.99 Stress management 3 (6) 0 0.23 0.94 Time management 5 (10) 0 0.33 1.08 Learning 4 (8) 0 0.27 1.03 Motivation Incentives 13 (25) 0 0.65 1.37 Barriers 7 (13) 0 0.44 1.26 Risks 10 (19) 0 0.62 1.39 Goal-setting 36 (69) 4 2.25 1.87 Self-reward 23 (44) 0 1.77 2.01 Readiness 9 (17) 0 0.5 1.18 Self-talk 4 (8) 0 0.31 1.08 Self-efficacy 9 (17) 0 0.63 1.46 Norms 3 (6) 0 0.17 0.79 Opportunity/trigger Peer pressure 18 (35) 0 1.33 1.89 Modeling 16 (31) 0 0.83 1.50 Relapse prevention 2 (4) 0 0.10 0.57 Follow-up 6 (12) 0 0.38 1.09 Guilt 4 (8) 0 0.19 0.79 Stimulus control 4 (8) 0 0.25 0.95 However, SuperBetter, which had the highest HBT score, also Price and HBT had the highest price (Figure 1, Table 5). There was no association between price and HBT (Spearman correlation coefficient R =0.09641, P=.5010) (Figure 1). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 5 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Figure 1. Price and HBT score. Table 5. Physical activity games by price. Price (US$) Apps 0 34 0.99 6 1.99 5 2.99 4 3.99 1 4.99 2 All of the elements of gamification were present in the sample, Gamification Elements and HBT except for real-world prizes. The most common gamification The number of elements of gamification was not associated elements in the sample were fantasy environment (96%, 50/52), with HBT score (Spearman correlation coefficient R =.094, whereas storyline was present in half of the sample (50%, P=.5074; Figure 2). 26/52). Rankings or standings (19%, 10/52) and leaderboards (29%, 15/50) were the least commonly utilized feature of gamification in the sample (Table 6). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 6 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 6. Gamification elements (N=52). Gamification elements n (%) Storyline 26 (50) Fantasy environment 50 (96) Competition 31 (60) Possibility of failure 43 (83) Leaderboards 15 (29) Clear expectations 49 (94) Score 38 (73) Ranking or standing 10 (19) Levels 24 (46) Real world prizes 0 (0) Figure 2. Gamification and HBT score. was 37, and the average HBT score became 13.78. In other Discussion content analyses of non-game mobile phone apps that utilized the same coding rubric as this study, the average HBT score Principal Findings was lower; in a sample of physical activity apps, Cowan et al The purpose of our study was to determine the presence of HBT [28] reported an average HBT score of 10.01 out of 100, with in physical activity games developed for a mobile phone a high score of 28. Similarly, West et al [30] reported in a platform. This study also analyzed (1) the prevalence of specific sample of diet apps an average HBT score of 6.19 out of 100, health behavior constructs, (2) the association between price with a high score of 26. Other content analyses of health and and presence of HBT, and (3) the association between elements fitness non-game apps, including smoking cessation and weight of gamification and HBT in these same apps. loss apps, similarly demonstrate low levels of evidence-based health behavior change techniques [31,32,41]. There exist few The presence of HBT in this sample varied and many of the content analyses of serious games for health, let alone serious apps contained low levels of HBT, but HBT levels were higher health games developed for a mobile phone platform, but on average than HBT levels in analyses of non-game health exergames in general may contain relatively high levels of HBT. apps. The average HBT score of this sample was 14.98 out of Lyons et al [33] conducted a content analysis of physical activity 100, with SuperBetter, an outlier, yielding the highest HBT video games and found significant levels of HBT elements score at 76. Excluding SuperBetter, the next highest HBT score http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 7 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al present, such as performance feedback and modeling. Given [47] noted in a sample of apps utilized in physical activity and the limited research on HBT in non-game and serious game diet interventions that almost all (93%) were designed with health apps developed for mobile phones, it is difficult to some preconceived behavioral theory or construct. However, determine at present whether the latter contain higher levels of despite the relatively high levels of HBT in this sample, it is HBT, though this study provides evidence to support this likely these apps were not designed around HBT, especially as hypothesis. it appeared the majority were not designed for formal health interventions. Additionally, as suggested by Cowan et al [28], SuperBetter, an app used for achieving nonspecific health goals, app developers come from varied backgrounds and may not was an outlier with a much higher HBT score than the sample have formal training in HBT. It may be that app-based serious average. SuperBetter was unique in its heavy inclusion of games lend themselves well to inclusion of HBT by virtue of educational elements, including individually tailored assistance; design, whether it is consciously included or not. it required feedback on not only whether users completed each exercise, but also how well users completed each exercise, as Paid apps were no more likely to include elements of HBT than well as tips for improvement [42] (Figure 3). free apps. However, the sample of paid apps was small and these results should be interpreted with this limitation in mind. SuperBetter stands in stark contrast to physical activity app West et al [31] and Cowan et al [28] conducted a similar content games focused more on entertainment with few educational analysis of paid health and fitness apps and reported that apps elements, such as GPS Invaders (Figure 4). exceeding US $0.99 in price were more likely to contain Despite the differences in content, both SuperBetter and GPS elements of behavioral theory [28,31]. Similarly, Abroms et al Invaders are considered serious games as determined by the [41] found in a content analysis of tobacco cessation apps that inclusion criteria of this study. It should also be noted that the paid apps were more likely to include evidence-based practices coding rubric and inclusion criteria utilized in this study for tobacco cessation, suggesting that there may be a relationship emphasized the importance of educational content, in between quality and price for apps. While there was no overall conjunction with the definition of serious games as primarily association between price and HBT in this study, SuperBetter, intended to educate, rather than entertain [1,19]; other definitions which had the highest HBT score, was also the most expensive of serious games exist that place even less of an emphasis on app. It is important for consumers and health professionals to educational elements [43]. It is unclear whether serious games avoid assuming that paid fitness games associated with a for health require high levels of education in order to be well-known or popular organizations are more efficacious. efficacious. While games like SuperBetter contain higher levels Affiliation with a professional organization does not always of educational content and HBT and research suggests that imply validity. Given the wide variance in expertise of app interventions based in theory are more likely to lead to lasting developers, research and evaluation of health apps by both behavior change, it is worth considering whether industries and independent researchers are important to entertainment-based games such as GPS Invaders [44] could determine how to design apps that will change health behaviors be more effective in changing behavior than educational games, in the long-term. Furthermore, health app designers would do as they may be more popular and engaging in the long-term. well to partner with health behavior experts. The interplay between educational and entertainment elements There was also no significant association between elements of is an important area of study for serious game researchers [45]. gamification and presence of other HBT constructs—that is, There must be a balance between educational and entertainment having more game elements did not increase the overall HBT elements in games to maximize player motivation and score. Researchers disagree on definitions of serious games, engagement [46]. Further research on the relative importance and the number and type of gamification elements needed to of educational versus entertainment elements in serious games merit the classification of a serious game vary [50]. Many for health in long-term behavior change should be conducted. legitimate serious games may not contain high levels of The most prevalent health behavior constructs (after traditional game-like elements. Current research indicates that gamification elements) included goal setting, self-monitoring, available health and fitness apps contain significant amounts and self-reward. In a review of mobile apps utilized in health of gamification elements [15], but these same apps do not appear interventions, Payne et al [47] found that self-monitoring was to contain high levels of HBT [28,30,31]. There appears to be the most commonly utilized health behavior construct, followed a difference in HBT content between physical activity games by cues to action and feedback. The use of self-monitoring in apps and non-game apps, but it seems this relationship is not physical activity interventions has been found to be one of the linear (it is not the case that the more gamified the app, the more strongest predictors of success in behavior change [48], and behavioral theory components it contains). Assuming it is true goal-setting is commonly utilized and shows promise in physical that serious health game apps are naturally better suited for HBT activity and obesity interventions [49]. Lyons et al [33] also than nongame apps, it is unclear how many elements of found that some of the most common HBT elements in physical gamification a game must have, or which specific gamification activity video games included feedback, modeling, rewards, elements are required, for this relationship to hold true. and self-monitoring. While many of the apps in this sample The findings of our study are significant for practical use in scored fairly high in HBT and contained many HBT components public health, especially as mobile apps are being increasingly shown to be effective in health behavior change, it is unclear utilized in health interventions [47]. While some researchers whether the app designers consciously designed the physical argue that current health behavior models are flawed [51], activity games with behavioral theories in mind. Payne et al historically, designing theory-based public health interventions http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 8 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al has been widely accepted as essential for lasting health behavior constructs such as perceived benefit of and barriers to attending change [23]. Similarly, researchers indicate that mobile phone appointments are not also addressed, the app will likely not be health interventions that incorporate health behavior elements enough to prompt behavior changes [51]. It could be argued are more efficacious than non-theory based interventions that mobile phone games—far more complex than text message [51-53]. Riley et al argues that it is essential to utilize health interventions—may also require a theoretically based orientation behavior models in even the simplest of mobile phone for effectiveness in changing health behavior, though as interventions, such as a text message reminder intervention to mentioned previously, the dual nature of serious games as both increase attendance to medical appointments. Although this educational and entertainment tools may complicate this intervention incorporates built-in cues to action, if theoretical relationship. Figure 3. SuperBetter. http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 9 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Figure 4. GPS Invaders. the description of a game via the description; the coders found Limitations that none of these games fit the definition of a serious game, so The findings of our study should be interpreted in the context the likelihood that apps were overlooked due to weaknesses in of some limitations. First, the coders only used the mobile phone the description appears low. Finally, it should be noted that the for either 1 level or 30 minutes to code for HBT elements. It is definition of a serious game is not consistent across research; possible that some HBT components were missed by limiting a number of legitimate serious exercise games exist that do not use to this time frame, though unlikely; a recent study fulfill the criteria we proposed. Legitimate exergames (according demonstrates that while mobile phone and app use is increasing, to other researchers) may have been excluded from our sample. average app session length has stayed constant at about 5.7 In this particular study, we were more interested in games minutes [54]. The coders spent over five times that amount emphasizing education, though content analyses of serious coding each app, so the chances of missing unique or important games with different criteria would be interesting for future HBT components appear low. Additionally, the final sample research. size was small, though this was difficult to avoid, as health app Conclusions games are still a recent development. The coders conducted a thorough search, including the first 500 apps for every search Physical activity health games developed for mobile phones are term, to capture as many existing physical activity games as a potentially viable option for health interventions, though possible. While the sample could have been expanded upon to further research and development of such games should include other app games related to health (e.g., diet, nutrition), continue. Further research should be conducted to determine exclusively physical activity apps were chosen because previous whether these health games are efficacious in health content analyses of health apps have been similarly restrictive interventions, and the extent to which educational and in scope [28,30], and addressing only physical activity games gamification elements impact efficacy should be further assessed was more conducive to direct comparison between both these as well. Collaboration between app designers and behavioral previous content analyses and studies of exergames. specialists is also crucial to help promote lasting behavior change. Investigations into whether serious app games for health The coders analyzed only app descriptions to determine if each are more conducive to inclusion of HBT and whether they app qualified as a health game, and it is possible that some universally contain more elements of HBT is valuable in order games were missed due to inadequate descriptions. The coders to assess whether such games can improve individual and attempted to compensate for this limitation by selecting a sample community health in the long-term. (10 apps) that appeared in the search but did not appear to meet Conflicts of Interest None declared. References 1. Michael D, Chen S. Serious Games: Games That Educate, Train, and Inform. Independence, KY: Cengage Learning PTR; http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 10 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al 2. Stapleton A. 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Time in App Increases by 21% Across All Apps. 2014 URL: http://info.localytics.com/blog/ time-in-app-increases-by-21-across-all-apps [accessed 2014-12-28] [WebCite Cache ID 6V9jwet1K] Edited by G Eysenbach; submitted 28.12.14; peer-reviewed by E Lyons, C Lister; comments to author 15.01.15; revised version received 10.05.15; accepted 24.05.15; published 13.07.15 Please cite as: Payne HE, Moxley VBA, MacDonald E JMIR Serious Games 2015;3(2):e4 URL: http://games.jmir.org/2015/2/e4/ doi: 10.2196/games.4187 PMID: 26168926 ©Hannah E Payne, Victor BA Moxley, Elizabeth MacDonald. Originally published in JMIR Serious Games (http://games.jmir.org), 13.07.2015. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on http://games.jmir.org, as well as this copyright and license information must be included. http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 13 (page number not for citation purposes) XSL FO RenderX http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JMIR Serious Games JMIR Publications

Health Behavior Theory in Physical Activity Game Apps: A Content Analysis

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Background: Physical activity games developed for a mobile phone platform are becoming increasingly popular, yet little is known about their content or inclusion of health behavior theory (HBT). Objective: The objective of our study was to quantify elements of HBT in physical activity games developed for mobile phones and to assess the relationship between theoretical constructs and various app features. Methods: We conducted an analysis of exercise and physical activity game apps in the Apple App Store in the fall of 2014. A total of 52 apps were identified and rated for inclusion of health behavior theoretical constructs using an established theory-based rubric. Each app was coded for 100 theoretical items, containing 5 questions for 20 different constructs. Possible total theory scores ranged from 0 to 100. Descriptive statistics and Spearman correlations were used to describe the HBT score and association with selected app features, respectively. Results: The average HBT score in the sample was 14.98 out of 100. One outlier, SuperBetter, scored higher than the other apps with a score of 76. Goal setting, self-monitoring, and self-reward were the most-reported constructs found in the sample. There was no association between either app price and theory score (P=.5074), or number of gamification elements and theory score (P=.5010). However, Superbetter, with the highest HBT score, was also the most expensive app. Conclusions: There are few content analyses of serious games for health, but a comparison between these findings and previous content analyses of non-game health apps indicates that physical activity mobile phone games demonstrate higher levels of behavior theory. The most common theoretical constructs found in this sample are known to be efficacious elements in physical activity interventions. It is unclear, however, whether app designers consciously design physical activity mobile phone games with specific constructs in mind; it may be that games lend themselves well to inclusion of theory and any constructs found in significant levels are coincidental. Health games developed for mobile phones could be potentially used in health interventions, but collaboration between app designers and behavioral specialists is crucial. Additionally, further research is needed to better characterize mobile phone health games and the relative importance of educational elements versus gamification elements in long-term behavior change. (JMIR Serious Games 2015;3(2):e4) doi: 10.2196/games.4187 KEYWORDS health and fitness apps; mobile phone; behavioral health; theory; content analysis; physical activity http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 1 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al contained few evidence-based practices, and Cowan et al [28] Introduction reported in a content analysis of physical activity apps that the sample contained low levels of HBT, suggesting that the lack Serious games, or games whose primary purpose is to educate of behavioral components may have been due to the widely rather than entertain [1], have become a popular research focus varying professional backgrounds of app developers. because of their potential application in fields such as education, Conversely, in a content analysis of physical activity video military, business, and health and wellness [2]. Games appear games, Lyons et al [33] reported that the games contained a to be an emerging option for behavioral change, especially relatively high percentage of health behavior constructs [33]. health behaviors, as serious games address innate psychological It may be that serious health games in general contain high needs while offering intrinsic motivation in the form of fun [3]. amounts of HBT, whether HBT is consciously included or Serious games may also have potential to impact health behavior because games by design are more conducive to inclusion of change on a widespread level because of their appeal and the HBT, though there has not been enough research conducted to popularity of gaming. Furthermore, 59% of Americans play determine whether this is true. video games, and the average household owns at least one game console, PC, or mobile phone [4]. Serious games have been As health professionals are increasingly using mobile phone increasingly utilized in public health interventions [5], and many apps in interventions to increase physical activity, research on have shown promise in changing behavior in areas such as the content of such apps is important. Although many content tobacco cessation, violence prevention, and mental health [6-8]. analyses for health and fitness apps have been recently conducted [26-31] and analyses of exergames are emerging Serious games for public health have typically been developed [33], currently, no studies have been conducted to investigate as video games [9,10]. Exergames, or video games that require HBT in serious games developed for mobile phones. The physical movement in order to play, are a particularly popular purpose of our study was to identify the currently available most tool for health professionals especially as physical activity popular physical activity health games developed for mobile among the US population has decreased and chronic diseases phones and to conduct a content analysis of HBT in these games. such as obesity have increased [11-13]. While serious games were initially designed for personal computers and more recently Methods for gaming systems, mobile phones are another increasingly viable platform for health and physical fitness games for several Study Design reasons. First, mobile phones are widely used; mobile phone Our study was a content analysis of HBT contained in physical use increased 22% over the year 2013 alone, and among US activity game apps selected from among the apps available in households that own a device to play video games, 53% play the iTunes App Store’s Health and Fitness category. Two games on a mobile phone [4]. Second, game-like elements are graduate students trained in HBT coded the apps. already frequently utilized by health app developers. Lister et al found that elements of gamification, or the “use of game Sample Identification design elements in non-game contexts” [14], appeared in a large The sample was collected from the Apple App Store in the fall percentage of health and fitness apps [15]. Third, the use of of 2014. Apps designed for iPhone use were chosen, because apps in health interventions is already prevalent among public many similar app content analyses have used Apple’s App store health professionals [16-18], and interventions using serious for sample selection [27,28,30,31]. This sample contained apps health games on mobile phones are emerging as well [19-21]. categorized under the health and fitness section of the App Store The few health behavior change interventions that have utilized and were related to physical activity. Physical activity mobile serious games developed for a mobile phone platform have phone games were selected for two reasons: (1) physical activity shown to improve health outcomes in areas such as diabetes is both an impactful and neglected health behavior [12,13], and management and healthy eating [19-21]. (2) interventions utilizing physical activity apps are a growing Much research suggests that health interventions designed area of interest for health researchers [34-37]. There were 42 around health behavior theory (HBT) are more effective in key search terms that were established prior to the sample changing behavior than those which are not [22-25]. Many collection, using key phrases for both physical activity and content analyses of health apps indicate that such apps generally games. Keywords included fitness terms such as “running”, contain low levels of HBT or are not adequately designed for “walking”, “workout”, “exercise”, and others related to these long-term behavior change [26-31]. For example, Breton et al behaviors, as well as game keywords, including “challenge”, [32] noted in a content analysis of weight-loss apps that most “adventure”, and “interactive” (Table 1). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 2 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 1. Search terms. Physical activity terms Gamification terms Dance Game Exercise Avatar Fitness Reality game Run Virtual Fit Challenge Team Race Train Quest Trainer Adventure Goal Interactive Walk Simulator Track Augmented reality Tracker Running Trek Workout Health Cycling Aerobics Cardio Weight training We have formal training in public health and health behavior Coding Procedure and adapted the search terms from a previous content analysis Each app selected for final inclusion was coded into an initial of health theory in fitness apps [28]. Search terms were entered sampling rubric using Qualtrics online survey software. The into the Apple App Store on iPads, as iPads allow filtering of coders downloaded each app to an iPad or iPhone and played results. Search results were narrowed by (1) iPhone only, (2) each game for a minimum of 30 minutes or until completing health and fitness, and (3) popularity. Previous content analyses one level to increase familiarity with the user interface and of apps ordered search results by popularity to ensure that the available functions. The coders then used a theory-based apps that were reviewed were highly used [15,28]. instrument to conduct the content analysis for each app. The first 500 most popular apps were chosen for each search Measurement term, as the app store does not sort by page number. The instrument and methodology used for coding was adapted Additionally, as adapted from Lister et al [15], searching through from an instrument used by Cowan et al [28] designed to assess a set number of primary results is enough for an adequate theoretical content of physical activity apps. A similar rubric sample, because users do not typically search beyond the first was used, with the addition of more questions about social few search pages [38,39]. networking sites utilized in the apps, expanding the options for The detailed written descriptions for the first 500 apps that type of exercise utilized in the app, and tailoring the items for appeared in the search results under each topic were analyzed a serious game setting. to assess whether each app met the criteria for a serious health Each app was coded using a rubric with 100 theoretical items, game. The definition for serious game was taken from containing five questions each for 20 different constructs, as definitions provided by Michael and Chen [1] and Shegog [19] used by Cowan et al [28]. The coding rubric required choosing and required that the app was primarily intended to educate, 0 points when the construct was not present in the app, 1 point rather than entertain, as well as change a health behavior; for generalized information on the construct, 2 points for additionally, each app needed to either (1) contain a fantasy assessing user’s knowledge relating to the construct, 3 points storyline or narrative, or (2) include the possibility of failure. for providing feedback about user’s knowledge on the construct, The initial search revealed 86 apps that were originally selected 4 points for general assistance relating to the construct, and 5 as meeting the criteria. After reviewing all of the apps, 52 were points for individualized assistance to improve relative to the identified for final inclusion. Apps were excluded that required construct. The points for each construct were added together special equipment (e.g., bikes, treadmills, pedometers, heart for each app. This resulted in a HBT score ranging from 0 to rate meters, GPS) (8), could not be located in the App Store upon subsequent searches (5), failed to operate (8), or upon We also coded for gamification elements. The specific further investigation did not meet the criteria for a physical gamification elements coded for were selected from an activity game (13). instrument used by Lister et al [15] and from the definition adapted from Michael and Chen [1] and Shegog [19] (Table 6). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 3 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al determine whether there was an association between HBT and Analysis price, as well as HBT and total number of gamification elements. Coded data were imported from Qualtrics and analyzed using SAS Studio. To verify the level of interrater reliability, both Results coders independently coded 10 common apps, approximately 12% (10/86) of the original sample and 19% (10/52) of those Sample Characteristics retained for final inclusion. A Cohen’s kappa coefficient, a Characteristics of the sample are shown in Table 2.The mean method commonly used in content analysis research, was HBT score was 14.98 out of 100 points. One of the apps, calculated to measure interrater agreement (κ=.60) with 97% SuperBetter, was an outlier with a much higher theory score agreement [15,28]. This is categorized as high-moderate than the rest of the sample (HBT score of 76 out of 100). Four agreement, which ranges from .41 to.60 and is an acceptable of the apps (GPS Invaders, MotionMaze Holiday Adventure, level of interrater agreement [40]. Descriptive statistics were Mapventures, and TrezrHunt Free) contained no HBT elements used to report on the integration of HBT into physical activity as dictated by the coding rubric. Walking (56%, 29/50) and mobile phone games. A Spearman correlation was used to running (42%, 22/50) were the most common exercises incorporated into apps (Table 3). Table 2. App characteristics. App name HBT score App name HBT score SuperBetter 76 Rare Candy—Epic Habit and Goa 12 Yoga Retreat 37 Rare candy free 12 Zombies, Run! 5k Training 35 Wokamon 12 iBelly Workout 29 Silk Road Walk 12 The Walk 29 Runno 11 Workout in a Bag—for kids 29 Box the Bag 9 Yes, Drill Sergeant! 28 Block Sports 9 RunAlice 28 Walky 8 Walk it! 24 AR Basketball 8 Zombies Run! 24 Battlesuit Runner Fitness 8 Ninja Fitness Free 24 Jump Boy 8 Streetquest—run a game 23 iBowl 8 Walk n' Play 22 MotionMaze Trick or Treat 7 Burn Your Fat with Me! 21 Hike the World—GPS Tracker 6 PushUp Club Free 20 MotionMaze 6 NFL Play 60 19 Paranoid 5 Habit Monster 17 treasure island GPS, 5 Turfly 17 AR Soccer 4 Daily Spartan 17 Keep Moving 4 Walkr—Galaxy Adventure in You 16 Pygmalions Challenge 1 FitQuest Lite 16 GPS Fun Lite 1 RunZombieRun 16 Gigaputt 1 7 Min Workout Zombie Survival 15 GPS Invaders 0 HuntedApp 14 MotionMaze Holiday Adventure 0 TapCloud 13 Mapventures 0 Superhero Workout 13 TrezrHunt Free 0 http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 4 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 3. Exercise type in apps. Forms of exercise n % Walking 29 56 Running 22 42 None/general movement 17 33 Weight lifting/bodyweight exercises 13 25 Other 9 17 Stretching 8 15 Jumping 5 10 (0-100). Goal setting, self-monitoring, and self-reward were the Presence of Specific HBT Constructs most-reported constructs found. Only self-monitoring and Table 4 shows the mean score (0-5) for the presence of HBT goal-setting had a median score greater than zero. For both, the constructs measured in the sample, as well as the overall score median score was 5. Table 4. HBT score by construct (N=52). HBT n (%) Median Mean SD Overall score 52 (100) 12.5 14.98 12.92 Capacity General information 20 (38) 0 1.48 1.99 Self-monitoring 30 (58) 4 2.25 1.99 Stress management 3 (6) 0 0.23 0.94 Time management 5 (10) 0 0.33 1.08 Learning 4 (8) 0 0.27 1.03 Motivation Incentives 13 (25) 0 0.65 1.37 Barriers 7 (13) 0 0.44 1.26 Risks 10 (19) 0 0.62 1.39 Goal-setting 36 (69) 4 2.25 1.87 Self-reward 23 (44) 0 1.77 2.01 Readiness 9 (17) 0 0.5 1.18 Self-talk 4 (8) 0 0.31 1.08 Self-efficacy 9 (17) 0 0.63 1.46 Norms 3 (6) 0 0.17 0.79 Opportunity/trigger Peer pressure 18 (35) 0 1.33 1.89 Modeling 16 (31) 0 0.83 1.50 Relapse prevention 2 (4) 0 0.10 0.57 Follow-up 6 (12) 0 0.38 1.09 Guilt 4 (8) 0 0.19 0.79 Stimulus control 4 (8) 0 0.25 0.95 However, SuperBetter, which had the highest HBT score, also Price and HBT had the highest price (Figure 1, Table 5). There was no association between price and HBT (Spearman correlation coefficient R =0.09641, P=.5010) (Figure 1). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 5 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Figure 1. Price and HBT score. Table 5. Physical activity games by price. Price (US$) Apps 0 34 0.99 6 1.99 5 2.99 4 3.99 1 4.99 2 All of the elements of gamification were present in the sample, Gamification Elements and HBT except for real-world prizes. The most common gamification The number of elements of gamification was not associated elements in the sample were fantasy environment (96%, 50/52), with HBT score (Spearman correlation coefficient R =.094, whereas storyline was present in half of the sample (50%, P=.5074; Figure 2). 26/52). Rankings or standings (19%, 10/52) and leaderboards (29%, 15/50) were the least commonly utilized feature of gamification in the sample (Table 6). http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 6 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Table 6. Gamification elements (N=52). Gamification elements n (%) Storyline 26 (50) Fantasy environment 50 (96) Competition 31 (60) Possibility of failure 43 (83) Leaderboards 15 (29) Clear expectations 49 (94) Score 38 (73) Ranking or standing 10 (19) Levels 24 (46) Real world prizes 0 (0) Figure 2. Gamification and HBT score. was 37, and the average HBT score became 13.78. In other Discussion content analyses of non-game mobile phone apps that utilized the same coding rubric as this study, the average HBT score Principal Findings was lower; in a sample of physical activity apps, Cowan et al The purpose of our study was to determine the presence of HBT [28] reported an average HBT score of 10.01 out of 100, with in physical activity games developed for a mobile phone a high score of 28. Similarly, West et al [30] reported in a platform. This study also analyzed (1) the prevalence of specific sample of diet apps an average HBT score of 6.19 out of 100, health behavior constructs, (2) the association between price with a high score of 26. Other content analyses of health and and presence of HBT, and (3) the association between elements fitness non-game apps, including smoking cessation and weight of gamification and HBT in these same apps. loss apps, similarly demonstrate low levels of evidence-based health behavior change techniques [31,32,41]. There exist few The presence of HBT in this sample varied and many of the content analyses of serious games for health, let alone serious apps contained low levels of HBT, but HBT levels were higher health games developed for a mobile phone platform, but on average than HBT levels in analyses of non-game health exergames in general may contain relatively high levels of HBT. apps. The average HBT score of this sample was 14.98 out of Lyons et al [33] conducted a content analysis of physical activity 100, with SuperBetter, an outlier, yielding the highest HBT video games and found significant levels of HBT elements score at 76. Excluding SuperBetter, the next highest HBT score http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 7 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al present, such as performance feedback and modeling. Given [47] noted in a sample of apps utilized in physical activity and the limited research on HBT in non-game and serious game diet interventions that almost all (93%) were designed with health apps developed for mobile phones, it is difficult to some preconceived behavioral theory or construct. However, determine at present whether the latter contain higher levels of despite the relatively high levels of HBT in this sample, it is HBT, though this study provides evidence to support this likely these apps were not designed around HBT, especially as hypothesis. it appeared the majority were not designed for formal health interventions. Additionally, as suggested by Cowan et al [28], SuperBetter, an app used for achieving nonspecific health goals, app developers come from varied backgrounds and may not was an outlier with a much higher HBT score than the sample have formal training in HBT. It may be that app-based serious average. SuperBetter was unique in its heavy inclusion of games lend themselves well to inclusion of HBT by virtue of educational elements, including individually tailored assistance; design, whether it is consciously included or not. it required feedback on not only whether users completed each exercise, but also how well users completed each exercise, as Paid apps were no more likely to include elements of HBT than well as tips for improvement [42] (Figure 3). free apps. However, the sample of paid apps was small and these results should be interpreted with this limitation in mind. SuperBetter stands in stark contrast to physical activity app West et al [31] and Cowan et al [28] conducted a similar content games focused more on entertainment with few educational analysis of paid health and fitness apps and reported that apps elements, such as GPS Invaders (Figure 4). exceeding US $0.99 in price were more likely to contain Despite the differences in content, both SuperBetter and GPS elements of behavioral theory [28,31]. Similarly, Abroms et al Invaders are considered serious games as determined by the [41] found in a content analysis of tobacco cessation apps that inclusion criteria of this study. It should also be noted that the paid apps were more likely to include evidence-based practices coding rubric and inclusion criteria utilized in this study for tobacco cessation, suggesting that there may be a relationship emphasized the importance of educational content, in between quality and price for apps. While there was no overall conjunction with the definition of serious games as primarily association between price and HBT in this study, SuperBetter, intended to educate, rather than entertain [1,19]; other definitions which had the highest HBT score, was also the most expensive of serious games exist that place even less of an emphasis on app. It is important for consumers and health professionals to educational elements [43]. It is unclear whether serious games avoid assuming that paid fitness games associated with a for health require high levels of education in order to be well-known or popular organizations are more efficacious. efficacious. While games like SuperBetter contain higher levels Affiliation with a professional organization does not always of educational content and HBT and research suggests that imply validity. Given the wide variance in expertise of app interventions based in theory are more likely to lead to lasting developers, research and evaluation of health apps by both behavior change, it is worth considering whether industries and independent researchers are important to entertainment-based games such as GPS Invaders [44] could determine how to design apps that will change health behaviors be more effective in changing behavior than educational games, in the long-term. Furthermore, health app designers would do as they may be more popular and engaging in the long-term. well to partner with health behavior experts. The interplay between educational and entertainment elements There was also no significant association between elements of is an important area of study for serious game researchers [45]. gamification and presence of other HBT constructs—that is, There must be a balance between educational and entertainment having more game elements did not increase the overall HBT elements in games to maximize player motivation and score. Researchers disagree on definitions of serious games, engagement [46]. Further research on the relative importance and the number and type of gamification elements needed to of educational versus entertainment elements in serious games merit the classification of a serious game vary [50]. Many for health in long-term behavior change should be conducted. legitimate serious games may not contain high levels of The most prevalent health behavior constructs (after traditional game-like elements. Current research indicates that gamification elements) included goal setting, self-monitoring, available health and fitness apps contain significant amounts and self-reward. In a review of mobile apps utilized in health of gamification elements [15], but these same apps do not appear interventions, Payne et al [47] found that self-monitoring was to contain high levels of HBT [28,30,31]. There appears to be the most commonly utilized health behavior construct, followed a difference in HBT content between physical activity games by cues to action and feedback. The use of self-monitoring in apps and non-game apps, but it seems this relationship is not physical activity interventions has been found to be one of the linear (it is not the case that the more gamified the app, the more strongest predictors of success in behavior change [48], and behavioral theory components it contains). Assuming it is true goal-setting is commonly utilized and shows promise in physical that serious health game apps are naturally better suited for HBT activity and obesity interventions [49]. Lyons et al [33] also than nongame apps, it is unclear how many elements of found that some of the most common HBT elements in physical gamification a game must have, or which specific gamification activity video games included feedback, modeling, rewards, elements are required, for this relationship to hold true. and self-monitoring. While many of the apps in this sample The findings of our study are significant for practical use in scored fairly high in HBT and contained many HBT components public health, especially as mobile apps are being increasingly shown to be effective in health behavior change, it is unclear utilized in health interventions [47]. While some researchers whether the app designers consciously designed the physical argue that current health behavior models are flawed [51], activity games with behavioral theories in mind. Payne et al historically, designing theory-based public health interventions http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 8 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al has been widely accepted as essential for lasting health behavior constructs such as perceived benefit of and barriers to attending change [23]. Similarly, researchers indicate that mobile phone appointments are not also addressed, the app will likely not be health interventions that incorporate health behavior elements enough to prompt behavior changes [51]. It could be argued are more efficacious than non-theory based interventions that mobile phone games—far more complex than text message [51-53]. Riley et al argues that it is essential to utilize health interventions—may also require a theoretically based orientation behavior models in even the simplest of mobile phone for effectiveness in changing health behavior, though as interventions, such as a text message reminder intervention to mentioned previously, the dual nature of serious games as both increase attendance to medical appointments. Although this educational and entertainment tools may complicate this intervention incorporates built-in cues to action, if theoretical relationship. Figure 3. SuperBetter. http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 9 (page number not for citation purposes) XSL FO RenderX JMIR SERIOUS GAMES Payne et al Figure 4. GPS Invaders. the description of a game via the description; the coders found Limitations that none of these games fit the definition of a serious game, so The findings of our study should be interpreted in the context the likelihood that apps were overlooked due to weaknesses in of some limitations. First, the coders only used the mobile phone the description appears low. Finally, it should be noted that the for either 1 level or 30 minutes to code for HBT elements. It is definition of a serious game is not consistent across research; possible that some HBT components were missed by limiting a number of legitimate serious exercise games exist that do not use to this time frame, though unlikely; a recent study fulfill the criteria we proposed. Legitimate exergames (according demonstrates that while mobile phone and app use is increasing, to other researchers) may have been excluded from our sample. average app session length has stayed constant at about 5.7 In this particular study, we were more interested in games minutes [54]. The coders spent over five times that amount emphasizing education, though content analyses of serious coding each app, so the chances of missing unique or important games with different criteria would be interesting for future HBT components appear low. Additionally, the final sample research. size was small, though this was difficult to avoid, as health app Conclusions games are still a recent development. The coders conducted a thorough search, including the first 500 apps for every search Physical activity health games developed for mobile phones are term, to capture as many existing physical activity games as a potentially viable option for health interventions, though possible. While the sample could have been expanded upon to further research and development of such games should include other app games related to health (e.g., diet, nutrition), continue. Further research should be conducted to determine exclusively physical activity apps were chosen because previous whether these health games are efficacious in health content analyses of health apps have been similarly restrictive interventions, and the extent to which educational and in scope [28,30], and addressing only physical activity games gamification elements impact efficacy should be further assessed was more conducive to direct comparison between both these as well. Collaboration between app designers and behavioral previous content analyses and studies of exergames. specialists is also crucial to help promote lasting behavior change. 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Time in App Increases by 21% Across All Apps. 2014 URL: http://info.localytics.com/blog/ time-in-app-increases-by-21-across-all-apps [accessed 2014-12-28] [WebCite Cache ID 6V9jwet1K] Edited by G Eysenbach; submitted 28.12.14; peer-reviewed by E Lyons, C Lister; comments to author 15.01.15; revised version received 10.05.15; accepted 24.05.15; published 13.07.15 Please cite as: Payne HE, Moxley VBA, MacDonald E JMIR Serious Games 2015;3(2):e4 URL: http://games.jmir.org/2015/2/e4/ doi: 10.2196/games.4187 PMID: 26168926 ©Hannah E Payne, Victor BA Moxley, Elizabeth MacDonald. Originally published in JMIR Serious Games (http://games.jmir.org), 13.07.2015. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on http://games.jmir.org, as well as this copyright and license information must be included. http://games.jmir.org/2015/2/e4/ JMIR Serious Games 2015 | vol. 3 | iss. 2 | e4 | p. 13 (page number not for citation purposes) XSL FO RenderX

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JMIR Serious Games – JMIR Publications

Published: Jul 13, 2015

Keywords: health and fitness apps; mobile phone; behavioral health; theory; content analysis; physical activity

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