scholarly journals Mobile Game�Based Digital Vaccine for Reducing Risk of Lifestyle Diseases (Preprint)

2018 ◽  
Author(s):  
Rema Padman ◽  
Yi-Chin Kato-Lin ◽  
Bhargav SriPrakash ◽  
Sross Gupta ◽  
Palak Narang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Video Games ◽  
Mobile Devices ◽  
Healthy Eating ◽  
Statistical Models ◽  
Food Choices ◽  
Game Play ◽  
Mobile Games ◽  
Mobile Game ◽  
Lifestyle Diseases

BACKGROUND There is a rising epidemic of pediatric obesity in the United States and worldwide. While many factors contribute to pediatric overweight and obesity, dietary decisions are a leading cause. Children spend many hours a day playing video games, mostly on mobile devices. Hence, personalized gamification and learnification on mobile devices have great potential to influence children’s dietary-lifestyle behaviors during the habit formation stage of early childhood. In fact, video games on mobile devices have become a platform through which children learn in a fun and enjoyable way. While there is some early evidence of the positive impact of neuropsychology-based, cartoon-styled, immersive video games on healthy eating behaviors in children, the mechanisms underlying these improved outcomes are yet to be understood. OBJECTIVE To design appropriate interventions in the game environment for children’s behavior formation and change, we need to learn more about the underlying patterns of player behaviors evidenced during gameplay through techniques of machine learning and stochastic optimization. Building on prior descriptive work, this study examines the impact of a diet and lifestyle focused mobile game on children’s game play patterns and associate these patterns with their actual food choices using machine learning and statistical models. METHODS Our dataset was generated from an IRB-approved, informed consent–based randomized controlled trial (RCT) with pre- and post-treatment measurements of almost 100 school children using fooya!, a novel mobile gaming, iOS/Android based App that is being developed as a low-risk and non-invasive “digital vaccine” for lifestyle diseases, for 2 exposures of 20 minutes each. Based on artificial intelligence, neuropsychology and cognitive behavior therapy, fooya! has been shown to deliver positive outcomes with respect to food choices, self-reported dietary choices, and healthy eating intentions. We first model the process of game playing at any level across all students as a discrete, time-homogeneous, first-order Markov chain with multiple states, each representing a status of the game. Process mining identifies distinct patterns in the game sequences and statistical models establish the relationship between game patterns combined with demographic and behavioral data with actual food choices at the end of the game. RESULTS We find strong evidence of the positive effect of the mobile game on actual food choices, just after 40 minutes of intervention exposure (T: 2.46; C: 1.10; P<.001). Analysis of children’s play patterns shows significant variations in game play mechanics among players. Regression analyses further reveal that more engaged, dynamic, and strategic game play patterns are associated with better actual food choices. CONCLUSIONS This study adds to the growing body of evidence that learning about healthy eating in a fun and exciting way via mobile games, acting as Digital Vaccines, can positively impact children’s actual food choices. While promising, additional RCTs in varied settings and deeper analysis of the resulting data are needed to confirm Digital Vaccines’ potential to reduce the long-term risk of nutrition related non-communicable diseases such as diabetes and cardiovascular disease, as well as health risks from the double burden of overweight vs malnutrition and under-nutrition by educating children regarding healthy lifestyle choices using mobile games.

scholarly journals Impact of Pediatric Mobile Game Play on Healthy Eating Behavior: Randomized Controlled Trial

10.2196/15717 ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. e15717
Author(s):  
Yi-Chin Kato-Lin ◽  
Uttara Bharath Kumar ◽  
Bhargav Sri Prakash ◽  
Bhairavi Prakash ◽  
Vasini Varadan ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Positive Impact ◽  
Controlled Trial ◽  
Food Choices ◽  
Unhealthy Food ◽  
Healthy Foods ◽  
Game Play ◽  
Mobile Games ◽  
Mobile Game ◽  
Randomized Controlled

Background Video and mobile games have been shown to have a positive impact on behavior change in children. However, the potential impact of game play patterns on outcomes of interest are yet to be understood, especially for games with implicit learning components. Objective This study investigates the immediate impact of fooya!, a pediatric dietary mobile game with implicit learning components, on food choices. It also quantifies children’s heterogeneous game play patterns using game telemetry and determines the effects of these patterns on players’ food choices. Methods We analyzed data from a randomized controlled trial (RCT) involving 104 children, aged 10 to 11 years, randomly assigned to the treatment group (played fooya!, a dietary mobile game developed by one of the authors) or the control group (played Uno, a board game without dietary education). Children played the game for 20 minutes each in two sessions. After playing the game in each session, the children were asked to choose 2 out of 6 food items (3 healthy and 3 unhealthy choices). The number of healthy choices in both sessions was used as the major outcome. We first compared the choice and identification of healthy foods between treatment and control groups using statistical tests. Next, using game telemetry, we determined the variability in game play patterns by quantifying game play measures and modeled the process of game playing at any level across all students as a Markov chain. Finally, correlation tests and regression models were used to establish the relationship between game play measures and actual food choices. Results We saw a significant main effect of the mobile game on number of healthy foods actually chosen (treatment 2.48, control 1.10; P<.001; Cohen d=1.25) and identified (treatment 7.3, control 6.94; P=.048; Cohen d=.25). A large variation was observed in children’s game play patterns. Children played an average of 15 game levels in 2 sessions, with a range of 2 to 23 levels. The greatest variation was noted in the proportion of scoring activities that were highly rewarded, with an average of 0.17, ranging from 0.003 to 0.98. Healthy food choice was negatively associated with the number of unhealthy food facts that children read in the game (Kendall τ=–.32, P=.04), even after controlling for baseline food preference. Conclusions A mobile video game embedded with implicit learning components showed a strong positive impact on children’s food choices immediately following the game. Game telemetry captured children’s different play patterns and was associated with behavioral outcomes. These results have implications for the design and use of mobile games as an intervention to improve health behaviors, such as the display of unhealthy food facts during game play. Longitudinal RCTs are needed to assess long-term impact. Trial Registration ClinicalTrials.gov NCT04082195; https://clinicaltrials.gov/ct2/show/NCT04082195, registered retrospectively.

scholarly journals Impact of Pediatric Mobile Game Play on Healthy Eating Behavior: Randomized Controlled Trial (Preprint)

2019 ◽  
Author(s):  
Yi-Chin Kato-Lin ◽  
Uttara Bharath Kumar ◽  
Bhargav Sri Prakash ◽  
Bhairavi Prakash ◽  
Vasini Varadan ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Positive Impact ◽  
Controlled Trial ◽  
Food Choices ◽  
Unhealthy Food ◽  
Healthy Foods ◽  
Game Play ◽  
Mobile Games ◽  
Mobile Game ◽  
Randomized Controlled

BACKGROUND Video and mobile games have been shown to have a positive impact on behavior change in children. However, the potential impact of game play patterns on outcomes of interest are yet to be understood, especially for games with implicit learning components. OBJECTIVE This study investigates the immediate impact of fooya!, a pediatric dietary mobile game with implicit learning components, on food choices. It also quantifies children’s heterogeneous game play patterns using game telemetry and determines the effects of these patterns on players’ food choices. METHODS We analyzed data from a randomized controlled trial (RCT) involving 104 children, aged 10 to 11 years, randomly assigned to the treatment group (played fooya!, a dietary mobile game developed by one of the authors) or the control group (played Uno, a board game without dietary education). Children played the game for 20 minutes each in two sessions. After playing the game in each session, the children were asked to choose 2 out of 6 food items (3 healthy and 3 unhealthy choices). The number of healthy choices in both sessions was used as the major outcome. We first compared the choice and identification of healthy foods between treatment and control groups using statistical tests. Next, using game telemetry, we determined the variability in game play patterns by quantifying game play measures and modeled the process of game playing at any level across all students as a Markov chain. Finally, correlation tests and regression models were used to establish the relationship between game play measures and actual food choices. RESULTS We saw a significant main effect of the mobile game on number of healthy foods actually chosen (treatment 2.48, control 1.10; <i>P</i>&lt;.001; Cohen <i>d</i>=1.25) and identified (treatment 7.3, control 6.94; <i>P</i>=.048; Cohen <i>d</i>=.25). A large variation was observed in children’s game play patterns. Children played an average of 15 game levels in 2 sessions, with a range of 2 to 23 levels. The greatest variation was noted in the proportion of scoring activities that were highly rewarded, with an average of 0.17, ranging from 0.003 to 0.98. Healthy food choice was negatively associated with the number of unhealthy food facts that children read in the game (Kendall τ=–.32, <i>P</i>=.04), even after controlling for baseline food preference. CONCLUSIONS A mobile video game embedded with implicit learning components showed a strong positive impact on children’s food choices immediately following the game. Game telemetry captured children’s different play patterns and was associated with behavioral outcomes. These results have implications for the design and use of mobile games as an intervention to improve health behaviors, such as the display of unhealthy food facts during game play. Longitudinal RCTs are needed to assess long-term impact. CLINICALTRIAL ClinicalTrials.gov NCT04082195; https://clinicaltrials.gov/ct2/show/NCT04082195, registered retrospectively.

Mobile Games

2011 ◽  
pp. 147-160
Author(s):  
Tommi Pelkonen
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Strategic Alliances ◽  
Business Models ◽  
Digital Games ◽  
Business Environment ◽  
Northern Europe ◽  
Mobile Games ◽  
Mobile Game ◽  
Game Developers

This chapter analyzes the development trends in a special field within multi-channel e-business, digital games designed for mobile devices. It presents frameworks with which to analyze business models, industry positions, and strategic alliances of mobile device game developers, publishers, and telco operators. The key conclusions of the paper are that: (1) game developers should focus more throughly in the creation of excellent and value-adding game titles for consumers; and (2) mobile operators and mobile game pubishers should work actively to create a feasible business environment for market actors and to encourage consumers to consume mobile games. Furthermore, the chapter suggests that the key location in mobile entertainment is shifting gradually from Northern Europe to Asian markets.

Mobile Games

2011 ◽  
pp. 2295-2306
Author(s):  
Tommi Pelkonen
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Strategic Alliances ◽  
Business Models ◽  
Digital Games ◽  
Business Environment ◽  
Northern Europe ◽  
Mobile Games ◽  
Mobile Game ◽  
Game Developers

This chapter analyzes the development trends in a special field within multi-channel e-business, digital games designed for mobile devices. It presents frameworks with which to analyze business models, industry positions, and strategic alliances of mobile device game developers, publishers, and telco operators. The key conclusions of the paper are that: (1) game developers should focus more throughly in the creation of excellent and value-adding game titles for consumers; and (2) mobile operators and mobile game pubishers should work actively to create a feasible business environment for market actors and to encourage consumers to consume mobile games. Furthermore, the chapter suggests that the key location in mobile entertainment is shifting gradually from Northern Europe to Asian markets.

Pengukuran Kualitas untuk Aplikasi Permainan pada Perangkat Bergerak berdasarkan ISO 9126

2014 ◽  
Vol 5 (2) ◽  
pp. 83-90
Author(s):  
Galang Amanda Dwi P. ◽  
R. Firman Insan M. ◽  
Siti Rochimah
Keyword(s):  
Mobile Devices ◽  
Software Quality ◽  
Analytic Hierarchy ◽  
Mobile Games ◽  
Mobile Game ◽  
Software Quality Management ◽  
Iso 9126 ◽  
Index Terms ◽  
Hierarchy Process

Today, the rise of the mobile game applications development is a major phenomenon in the development of the mobile technology. Along with those trends, there are studies related to the development of a mobile game which expect the development of mobile games can be better in terms of quality and a higher tendency on the market. One of the things that is crucial to determine the quality of a game application on mobile devices is the standard calculations and metrics. In this paper a framework to measure the quality of a game application on mobile devices based on the ISO 9126 standard is proposed. The characteristics of the ISO 9126 standard will be mapped to the characteristics possessed by the mobile game applications, and by using the Analytic Hierarchy Process, the significance value to each aspect the game application can be obtained and the metric can be built Index terms - Analytic Hierarcy Process, Game Application, Mobile Devices, ISO 9126, Software Quality Management

Recurrent Neural Networks for Predicting Mobile Device State

2019 ◽  
pp. 1028-1043
Author(s):  
Juan Manuel Rodriguez ◽  
Alejandro Zunino ◽  
Antonela Tommasel ◽  
Cristian Mateos
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Video Games ◽  
Mobile Devices ◽  
Mobile Device ◽  
Recurrent Neural Networks ◽  
Ad Hoc ◽  
Modern Life ◽  
Battery Charge ◽  
Current State

Nowadays, mobile devices are ubiquitous in modern life as they allow users to perform virtually any task, from checking e-mails to playing video games. However, many of these operations are conditioned by the state of mobile devices. Therefore, knowing the current state of mobile devices and predicting their future states is a crucial issue in different domains, such as context-aware applications or ad-hoc networking. Several authors have proposed to use different machine learning methods for predicting some aspect of mobile devices' future states. This chapter aims at predicting mobile devices' battery charge, whether it is plugged to A/C, and screen and WiFi state. To fulfil this goal, the current state of a mobile device can be regarded as the consequence of the previous sequence of states, meaning that future states can be predicted by known previous ones. This chapter focuses on using recurrent neural networks for predicting future states.

scholarly journals Mā te rongo ka mohio: Māori Pā Wars and Kaupapa Māori Methodology at the Interface of Video Games

2018 ◽  
pp. 71-85
Author(s):  
Huni Mancini
Keyword(s):  
Video Games ◽  
Mobile Devices ◽  
Video Game ◽  
Game Design ◽  
Political Systems ◽  
Game Development ◽  
Mobile Game ◽  
Development Methodology ◽  
Kaupapa Māori ◽  
Video Game Technology

This essay reviews Māori Pā Wars (2017), a te reo Māori mobile game developed for mobile devices by independent Māori-led video game company Metia Interactive. Through consideration of the historical struggle for cultural and te reo Māori revitalisation, this essay discusses the use of kaupapa Māori methodology to activate mātauranga Māori through gameplay. Situated within a wider global shift towards ‘indie’ game development and more pertinently ‘Indigenous game development,’ Māori Pā Wars is one of the first games to bring kaupapa Māori methodology to the interface of video game technology. Through analysis of game development methodology, mechanics, game design and the ubiquitous mobile medium, this essay outlines the ways Māori Pā Wars challenges a ‘literature of dominance.’ It concludes that the game borrows from remix and convergence cultures inherent to indie game development, thereby reflecting the way Māori technologies, social and political systems continue to adapt to a changing technological landscape.

scholarly journals Use of Artificial Intelligence and Machine Learning in Games

2020 ◽  
pp. 114-118
Author(s):  
Nachiket Jadhav ◽  
Aniket Matodkar ◽  
Anish Mandhare ◽  
Sujata Bhairnallykar
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Video Games ◽  
The Other ◽  
Hardware Support ◽  
Learning In Games ◽  
Game Play ◽  
Cost Efficient

With modern video games surpassing every set of expectations in terms of graphics, game play, mechanics and hardware support, Artificial Intelligence in video games has also come a long way, from when it was first implemented in 1951. Although every set of games has an AI unique to itself, many of the algorithms are now developed such that they can be implemented in various games without any major changes in coding. But this could lead to the players exploiting AI in a single game to break the other games as well. Though this could be easily fixed by changing some minor fragments of algorithms, it would very well be an efficient way of developing complex AI for many games at once. This paper focuses on providing a cost-efficient way to implement AI algorithms that would benefit most of the upcoming and future games that will depend on AI to make themselves more dynamic to the players. This is done by taking the examples of various AI algorithms implemented in games like Pacman, Dota2, Tom Clancy's- The Division and many more.

Mobile Game-Based Learning

2019 ◽  
pp. 809-824 ◽  
Author(s):  
Boaventura DaCosta ◽  
Soonhwa Seok ◽  
Carolyn Kinsell
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
Future Research ◽  
Game Based Learning ◽  
Mobile Games ◽  
Mobile Game

The massive spread of mobile computing is undeniable with the draw of mobile games reaching epic proportions. This popularity, along with the anytime, anywhere, and on-any-device characteristics of mobile computing has ignited mounting interest in the use of mobile games in educational contexts, as illustrated by a growing number of articles on this topic. This chapter offers a review of the research on mobile game-based learning (mGBL), citing mobile games that have been experimented with and/or used to explore learning. Although many of the studies to date have emphasized the location-based capabilities of mobile devices, the emerging research focused on mGBL is promising, showing that learning can take place through the use of these games. Future research, however, should look beyond individual devices and functionality, and place greater importance on pedagogy.

Recurrent Neural Networks for Predicting Mobile Device State

2018 ◽  
pp. 6658-6670
Author(s):  
Juan Manuel Rodriguez ◽  
Alejandro Zunino ◽  
Antonela Tommasel ◽  
Cristian Mateos
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Video Games ◽  
Mobile Devices ◽  
Mobile Device ◽  
Recurrent Neural Networks ◽  
Ad Hoc ◽  
Modern Life ◽  
Battery Charge ◽  
Current State

Nowadays, mobile devices are ubiquitous in modern life as they allow users to perform virtually any task, from checking e-mails to playing video games. However, many of these operations are conditioned by the state of mobile devices. Therefore, knowing the current state of mobile devices and predicting their future states is a crucial issue in different domains, such as context-aware applications or ad-hoc networking. Several authors have proposed to use different machine learning methods for predicting some aspect of mobile devices' future states. This work aims at predicting mobile devices' battery charge, whether it is plugged to A/C, and screen and WiFi state. To fulfil this goal, the current state of a mobile device can be regarded as the consequence of the previous sequence of states, meaning that future states can be predicted by known previous ones. This work focuses on using Recurrent Neural Networks for predicting future states.

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