Commercially Available Apps to Support Healthy Family Meals: User Testing of App Utility, Acceptability, and Engagement

Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges

BACKGROUND

Smartphone apps can aid consumers in making healthier and more sustainable food purchases. However, there is still a limited understanding of the different app design approaches and their impact on food purchase choices. An overview of existing food purchase choice apps and an understanding of common challenges can help speed up effective future developments.

OBJECTIVE

We examined the academic literature on food purchase choice apps and provided an overview of the design characteristics, opportunities, and challenges for effective implementation. Thus, we contribute to an understanding of how technologies can effectively improve food purchase choice behavior and provide recommendations for future design efforts.

METHODS

Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we considered peer-reviewed literature on food purchase choice apps within IEEE Xplore, PubMed, Scopus, and ScienceDirect. We inductively coded and summarized design characteristics. Opportunities and challenges were addressed from both quantitative and qualitative perspectives. From the quantitative perspective, we coded and summarized outcomes of comparative evaluation trials. From the qualitative perspective, we performed a qualitative content analysis of commonly discussed opportunities and challenges.

RESULTS

We retrieved 55 articles, identified 46 unique apps, and grouped them into 5 distinct app types. Each app type supports a specific purchase choice stage and shares a common functional design. Most apps support the product selection stage (selection apps; 27/46, 59%), commonly by scanning the barcode and displaying a nutritional rating. In total, 73% (8/11) of the evaluation trials reported significant findings and indicated the potential of food purchase choice apps to support behavior change. However, relatively few evaluations covered the selection app type, and these studies showed mixed results. We found a common opportunity in apps contributing to learning (knowledge gain), whereas infrequent engagement presents a common challenge. The latter was associated with perceived burden of use, trust, and performance as well as with learning. In addition, there were technical challenges in establishing comprehensive product information databases or achieving performance accuracy with advanced identification methods such as image recognition.

CONCLUSIONS

Our findings suggest that designs of food purchase choice apps do not encourage repeated use or long-term adoption, compromising the effectiveness of behavior change through nudging. However, we found that smartphone apps can enhance learning, which plays an important role in behavior change. Compared with nudging as a mechanism for behavior change, this mechanism is less dependent on continued use. We argue that designs that optimize for learning within each interaction have a better chance of achieving behavior change. This review concludes with design recommendations, suggesting that food purchase choice app designers anticipate the possibility of early abandonment as part of their design process and design apps that optimize the learning experience.

Barriers and enablers to the family meal across time; a grounded theory study comparing South Australian parents' perspectives

Family meals are positively associated with numerous beneficial health and social outcomes. Current discourse however claims that parents are faced with numerous barriers when trying to bring the family together to share a meal. Solutions for overcoming barriers to a positive shared family meal are often individualistic and do not address the systemic pressures and burdens families have faced for decades. The aim of this study was to explore the systemic and novel barriers and enablers to shared family meals as experienced by families across time. To achieve this, a qualitative study informed by grounded theory was conducted. Parents of South Australian families were recruited and interviewed in the 1990s, and a new sample of parents were recruited and interviewed in 2020. Transcripts were analysed using grounded theory and comparative analysis methods. Thirty-two parents from 16 families were interviewed in the 1990s, and 22 parents from 10 families in 2020. Ten factors were identified presenting as either enablers or barriers to the family meal, depending on the context they were experienced. Barriers and enablers were largely consistent across time. Scheduling and flexibility, children's disruptions and children's independence, privileges required to have family meals and motivation and commitment to the family meal were identified as persistent enablers and barriers across time. These findings indicate that parents are faced with similar challenges they have been facing for decades and are still not being adequately supported to execute family meals regularly. Recognising that factors present as either barriers or enablers to the family meal provides us with opportunities to transform barriers to enablers and support families to have regular, meaningful family meals.

Personalized Flexible Meal Planning for Individuals With Diet-Related Health Concerns: System Design and Feasibility Validation Study

BACKGROUND

Chronic diseases such as heart disease, stroke, diabetes, and hypertension are major global health challenges. Healthy eating can help people with chronic diseases manage their condition and prevent complications. However, making healthy meal plans is not easy, as it requires the consideration of various factors such as health concerns, nutritional requirements, tastes, economic status, and time limits. Therefore, there is a need for effective, affordable, and personalized meal planning that can assist people in choosing food that suits their individual needs and preferences.

OBJECTIVE

This study aimed to design an artificial intelligence (AI)-powered meal planner that can generate personalized healthy meal plans based on the user's specific health conditions, personal preferences, and status.

METHODS

We proposed a system that integrates semantic reasoning, fuzzy logic, heuristic search, and multicriteria analysis to produce flexible, optimized meal plans based on the user's health concerns, nutrition needs, as well as food restrictions or constraints, along with other personal preferences. Specifically, we constructed an ontology-based knowledge base to model knowledge about food and nutrition. We defined semantic rules to represent dietary guidelines for different health concerns and built a fuzzy membership of food nutrition based on the experience of experts to handle vague and uncertain nutritional data. We applied a semantic rule-based filtering mechanism to filter out food that violate mandatory health guidelines and constraints, such as allergies and religion. We designed a novel, heuristic search method that identifies the best meals among several candidates and evaluates them based on their fuzzy nutritional score. To select nutritious meals that also satisfy the user's other preferences, we proposed a multicriteria decision-making approach.

RESULTS

We implemented a mobile app prototype system and evaluated its effectiveness through a use case study and user study. The results showed that the system generated healthy and personalized meal plans that considered the user's health concerns, optimized nutrition values, respected dietary restrictions and constraints, and met the user's preferences. The users were generally satisfied with the system and its features.

CONCLUSIONS

We designed an AI-powered meal planner that helps people create healthy and personalized meal plans based on their health conditions, preferences, and status. Our system uses multiple techniques to create optimized meal plans that consider multiple factors that affect food choice. Our evaluation tests confirmed the usability and feasibility of the proposed system. However, some limitations such as the lack of dynamic and real-time updates should be addressed in future studies. This study contributes to the development of AI-powered personalized meal planning systems that can support people's health and nutrition goals.

Planting Seeds for the Future: Scoping Review of Child Health Promotion Apps for Parents

BACKGROUND

Increasingly, parents use child health promotion apps to find health information. An overview of child health promotion apps for parents currently does not exist. The scope of child health topics addressed by parent apps is thus needed, including how they are evaluated.

OBJECTIVE

This scoping review aims to describe existing reported mobile health (mHealth) parent apps of middle- to high-income countries that promote child health. The focus centers on apps developed in the last 5 years, showing how the reported apps are evaluated, and listing reported outcomes found.

METHODS

A scoping review was conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) guidelines to identify parent apps or web-based programs on child health promotion published between January 2016 and June 2021 in 5 databases: PubMed, ERIC, IEEE Xplore, Web of Science, and Google Scholar. Separate sources were sought through an expert network. Included studies were summarized and analyzed through a systematic and descriptive content analysis, including keywords, year of publication, country of origin, aims/purpose, study population/sample size, intervention type, methodology/method(s), broad topic(s), evaluation, and study outcomes.

RESULTS

In total, 39 studies met the inclusion criteria from 1040 database and 60 expert-identified studies. Keywords reflected the health topics and app foci. About 64% (25/39) of included studies were published after 2019 and most stemmed from the United States, Australian, and European-based research. Studies aimed to review or evaluate apps or conducted app-based study interventions. The number of participants ranged from 7 to 1200. Quantitative and qualitative methods were used. Interventions included 28 primary studies, 6 app feasibility studies, and 5 app or literature reviews. Eight separate topics were found: parental feeding and nutrition, physical activity, maternal-child health, parent-child health, healthy environment, dental health, mental health, and sleep. Study intervention evaluations cited behavior change theories in 26 studies and evaluations were carried out with a variety of topic-specific, adapted, self-developed, or validated questionnaires and evaluation tools. To evaluate apps, user input and qualitative evaluations were often combined with surveys and frequently rated with the Mobile App Rating Scale. Outcomes reported some positive effects, while several intervention studies saw no effect at all. Effectively evaluating changes in behavior through apps, recruiting target groups, and retaining app engagement were challenges cited.

CONCLUSIONS

New parents are a key target group for child health apps, but evaluating child health promotion apps remains a challenge. Whether tailored to parent needs or adapted to the specific topic, apps should be rooted in a transparent theoretical groundwork. Applicable lessons for parent apps from existing research are to tailor app content, include intuitive and adaptive features, and embed well-founded parameters for long-term effect evaluation on child health promotion.

Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.

User Perceptions of eHealth and mHealth Services Promoting Physical Activity and Healthy Diets: Systematic Review

Background

Physical activity and a diet that follows general recommendations can help to prevent noncommunicable diseases. However, most adults do not meet current recommended guidelines, and support for behavior change needs to be strengthened. There is growing evidence that shows the benefits of eHealth and mobile health (mHealth) services in promoting healthy habits; however, their long-term effectiveness is uncertain because of nonadherence.

Objective

We aimed to explore users’ perceptions of acceptability, engagement, and usability of eHealth and mHealth services that promote physical activity, healthy diets, or both in the primary or secondary prevention of noncommunicable diseases.

Methods

We conducted a systematic review with a narrative synthesis. We performed the literature search in PubMed, PsycINFO, and CINAHL electronic databases in February 2021 and July 2021. The search was limited to papers published in English between 2016 and 2021. Papers on qualitative and mixed method studies that encompassed eHealth and mHealth services for adults with a focus on physical activity, healthy diet, or both in the primary or secondary prevention of noncommunicable diseases were included. Three authors screened the studies independently, and 2 of the authors separately performed thematic analysis of qualitative data.

Results

With an initial finding of 6308 articles and the removal of 427 duplicates, 23 articles were deemed eligible for inclusion in the review. Based on users’ preferences, an overarching theme—eHealth and mHealth services provide value but need to be tailored to individual needs—and 5 subthemes—interactive and integrated; varying and multifunctional; easy, pedagogic, and attractive; individualized and customizable; and reliable—emerged.

Conclusions

New evidence on the optimization of digital services that promote physical activity and healthy diets has been synthesized. The findings represent users’ perceptions of acceptability, engagement, and usability of eHealth and mHealth services and show that services should be personalized, dynamic, easily manageable, and reliable. These findings can help improve adherence to digital health-promoting services.