Updating the Foodbot Factory serious game with new interactive engaging features and enhanced educational content.

Serious games (i.e., digital games designed for educational purposes) can foster positive learning attitudes and are increasingly used as educational tools. Foodbot Factory is a serious game application (app) that helps children learn about healthy eating based on Canada's Food Guide principles and has demonstrated to increase nutrition knowledge among this group. This paper describes the process followed to expand Foodbot Factory's educational content and integrate immersive technologies and innovative features into the app. The revision process, which was guided by the Obesity-Related Behavioral Intervention Trials model, included the following phases: first, an interdisciplinary team of nutrition scientists, education experts, and computer scientists analyzed data from the original pilot study, recently published literature, and feedback from stakeholders to define areas to improve Foodbot Factory. The five original Foodbot Factory modules were evaluated by the team during weekly meetings, where the educational content, interactive features, and other elements that required updates (e.g., aesthetics and accessibility) were identified. Second, prototypes were created and refined until a final version of Foodbot Factory was approved. Nineteen children tested the updated Foodbot Factory and found it "easy to use" (89%) and "fun" (95%). The new version of Foodbot Factory contains 19 learning objectives, including 13 original and six new objectives. Interactive engagement features in the updated Foodbot Factory included augmented reality incorporated into two learning modules; new mini-games were created, including a memory game; an overhaul of the aesthetics; (e.g., new food images); and accessibility features were included to support users with cognitive and vision disabilities.

Impact of mHealth Interventions on Supporting Dietary Adherence in Cardiovascular Disease: A Systematic Review.

INTRODUCTION: A systematic review was conducted to determine if mobile health (mHealth) interventions, and which intervention characteristics, effectively support dietary adherence and reduce risk factors in patients with cardiovascular disease (CVD). METHOD: Using 7 databases, studies involving adult participants with specific CVD diagnoses, mHealth intervention testing, and dietary adherence assessment were identified. Systematic reviews, qualitative studies, or studies testing interventions involving open dialogue between participants and health care providers or researchers were excluded. Two independent reviewers conducted screening and assessed the risk of bias. RESULTS: Thirteen studies involved participants with prehypertension (n = 1), hypertension (n = 9), coronary artery disease (n = 2), and heart failure (n = 1). mHealth interventions in 8 studies improved dietary adherence, 4 showed mixed results, and 1 showed no improvements. Eight studies found interactive text and/or application-based mHealth intervention features effectively improved dietary adherence. One study had a low risk of bias, 2 had some concerns/moderate risk, and 10 had a high/critical or serious risk. DISCUSSION: In most included studies, mHealth interventions positively impacted dietary adherence for patients with CVD. IMPLICATIONS FOR RESEARCH AND PRACTICE: Clinicians may recommend mHealth interventions to support nutrition education and self-management for their patients with CVD.

The Content, Quality, and Behavior Change Techniques in Nutrition-Themed Mobile Apps for Children in Canada: App Review and Evaluation Study.

BACKGROUND: Children increasingly use mobile apps. Strategies to increase child engagement with apps include the use of gamification and images that incite fun and interaction, such as food. However, the foods and beverages that children are exposed to while using apps are unknown and may vary by app type. OBJECTIVE: The aim of this study is to identify the app content (ie, types of foods and beverages) included in nutrition-themed apps intended for children, to assess the use of game-like features, and to examine app characteristics such as overall quality and behavior change techniques (BCTs). METHODS: This analysis used a cross-sectional database of nutrition-themed apps intended for children (≤12 years), collected between May 2018 and June 2019 from the Apple App Store and Google Play Store (n=259). Apps were classified into four types: food games or nongames that included didactic nutrition guides, habit trackers, and other. Food and beverages were identified in apps and classified into 16 food categories, as recommended (8/16, 50%) and as not recommended (8/16, 50%) by dietary guidelines, and quantified by app type. Binomial logistic regression assessed whether game apps were associated with foods and beverages not recommended by guidelines. App quality, overall and by subscales, was determined using the Mobile App Rating Scale. The BCT Taxonomy was used to classify the different behavioral techniques that were identified in a subsample of apps (124/259, 47.9%). RESULTS: A total of 259 apps displayed a median of 6 (IQR 3) foods and beverages. Moreover, 62.5% (162/259) of apps were classified as food games, 27.4% (71/259) as didactic nutrition guides, 6.6% (17/259) as habit trackers, and 3.5% (9/259) as other. Most apps (198/259, 76.4%) displayed at least one food or beverage that was not recommended by the dietary guidelines. Food game apps were almost 3 times more likely to display food and beverages not recommended by the guidelines compared with nongame apps (ß=2.8; P<.001). The overall app quality was moderate, with a median Mobile App Rating Scale score of 3.6 (IQR 0.7). Functionality was the subscale with the highest score (median 4, IQR 0.3). Nutrition guides were more likely to be educational and contain informative content on healthy eating (score 3.7), compared with the other app types, although they also scored significantly lower in engagement (score 2.3). Most apps (105/124, 84.7%) displayed at least one BCT, with the most common BCT being information about health consequences. CONCLUSIONS: Findings suggest nutrition-themed apps intended for children displayed food and beverage content not recommended by dietary guidelines, with gaming apps more likely to display not recommended foods than their nongame counterparts. Many apps have a moderate app quality, and the use of consequences (instead of rewards) was the most common BCT.

Optimizing Child Nutrition Education With the Foodbot Factory Mobile Health App: Formative Evaluation and Analysis.

BACKGROUND: Early nutrition interventions to improve food knowledge and skills are critical in enhancing the diet quality of children and reducing the lifelong risk of chronic disease. Despite the rise of mobile health (mHealth) apps and their known effectiveness for improving health behaviors, few evidence-based apps exist to help engage children in learning about nutrition and healthy eating. OBJECTIVE: This study aimed to describe the iterative development and user testing of Foodbot Factory, a novel nutrition education gamified app for children to use at home or in the classroom and to present data from user testing experiments conducted to evaluate the app. METHODS: An interdisciplinary team of experts in nutrition, education (pedagogy), and game design led to the creation of Foodbot Factory. First, a literature review and an environmental scan of the app marketplace were conducted, and stakeholders were consulted to define the key objectives and content of Foodbot Factory. Dietitian and teacher stakeholders identified priority age groups and learning objectives. Using a quasi-experimental mixed method design guided by the Iterative Convergent Design for Mobile Health Usability Testing approach, five app user testing sessions were conducted among students (ages 9-12 years). During gameplay, engagement and usability were assessed via direct observations with a semistructured form. After gameplay, qualitative interviews and questionnaires were used to assess user satisfaction, engagement, usability, and knowledge gained. RESULTS: The environmental scan data revealed that few evidence-based nutrition education apps existed for children. A literature search identified key nutrients of concern for Canadian children and techniques that could be incorporated into the app to engage users in learning. Foodbot Factory included characters (2 scientists and Foodbots) who initiate fun and engaging dialogue and challenges (minigames), with storylines incorporating healthy eating messages that align with the established learning objectives. A total of five modules were developed: drinks, vegetables and fruit, grain foods, animal protein foods, and plant protein foods. Seven behavior change techniques and three unique gamified components were integrated into the app. Data from each user testing session were used to inform and optimize the next app iteration. The final user testing session demonstrated that participants agreed that they wanted to play Foodbot Factory again (12/17, 71%), that the app is easy to use (12/17, 71%) and fun (14/17, 88%), and that the app goals were clearly presented (15/17, 94%). CONCLUSIONS: Foodbot Factory is an engaging and educational mHealth intervention for the Canadian public that is grounded in evidence and developed by an interdisciplinary team of experts. The use of an iterative development approach is a demonstrated method to improve engagement, satisfaction, and usability with each iteration. Children find Foodbot Factory to be fun and easy to use, and can engage children in learning about nutrition.

The Effectiveness of the Foodbot Factory Mobile Serious Game on Increasing Nutrition Knowledge in Children.

The interactive and engaging nature of serious games (i.e., video games designed for educational purposes) enables deeper learning and facilitates behavior change; however, most do not specifically support the dissemination of national dietary guidelines, and there are limited data on their impact on child nutrition knowledge. The Foodbot Factory serious game mobile application was developed to support school children in learning about Canada's Food Guide; however, its impacts on nutrition knowledge have not been evaluated. The objective of this study was to determine if Foodbot Factory effectively improves children's knowledge of Canada's Food Guide, compared to a control group (control app). This study was a single-blinded, parallel, randomized controlled pilot study conducted among children ages 8-10 years attending Ontario Tech University day camps. Compared to the control group (n = 34), children who used Foodbot Factory (n = 39) had significant increases in overall nutrition knowledge (10.3 ± 2.9 to 13.5 ± 3.8 versus 10.2 ± 3.1 to 10.4 ± 3.2, p < 0.001), and in Vegetables and Fruits (p < 0.001), Protein Foods (p < 0.001), and Whole Grain Foods (p = 0.040) sub-scores. No significant difference in knowledge was observed in the Drinks sub-score. Foodbot Factory has the potential to be an effective educational tool to support children in learning about nutrition.