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A Review of Critical Features and General Issues of Freely Available mHealth Apps For Dietary Assessment

Obesity is known to lower the quality of life substantially. It is often associated with increased chances of non-communicable diseases such as diabetes, cardiovascular problems, various cancers, etc. Evidence suggests that diet-related mobile applications play a vital role in assisting individuals in making healthier choices and keeping track of food intake. However, due to an abundance of similar applications, it becomes pertinent to evaluate each of them in terms of functionality, usability, and possible design issues to truly determine state-of-the-art solutions for the future. Since these applications involve implementing multiple user requirements and recommendations from different dietitians, the evaluation becomes quite complex. Therefore, this study aims to review existing dietary applications at length to highlight key features and problems that enhance or undermine an application's usability. For this purpose, we have examined the published literature from various scientific databases of the PUBMED, CINAHL (January 2010-December 2019) and Science Direct (2010-2019). We followed PRISMA guidelines, and out of our findings, fifty-six primary studies met our inclusion criteria after identification, screening, eligibility and full-text evaluation. We analyzed 35 apps from the selected studies and extracted the data of each of the identified apps.Following our detailed analysis on the comprehensiveness of freely available mHealth applications, we specified potential future research challenges and stated recommendations to help grow clinically accurate diet-related applications.

Despite considerable advancements in medicine today, the number of people getting affected by chronic diseases is significantly greater due to unhealthy lifestyles. Obesity is one of the most common contributing factors to chronic diseases, affecting almost every part of the world from middle to lower-income countries. According to a survey in 2016, 1.9 billion adults aged 18 years and older were overweight (1). The prevalence of the aforementioned diseases poses serious concerns. However, determining the right remedial measures is dependent on different factors ranging from a person's genetics to lifestyle, which need to be adjusted according to the cause and severity of the condition. Treatment may include medication, lifestyle changes (87) such as choosing healthier food alternatives, exercise, and requiring patients to follow a customized diet plan (88).
On the other hand, with rapid technological advancements and increased usage of handheld devices such as smartphones, tablets, and smartwatches, people's reliance on these devices has undoubtedly grown beyond their utility as a means to communicate. The number of mobile users in 2012 for Android and iOS devices (2) increased from 640 million to 2,562 million in 2016 (3). These days, smartphone applications are being extended to support electronic healthcare practices (4), (5), and evidence across several fields show promising results which support the feasibility, acceptability and efficacy of digital health interventions in different medical conditions. These conditions include but not limited to managing adolescent health and wellness (92), interventions in sickle cell disease (94), pediatric cancer (93) (97), chronic health conditions (95) and improving adherence to preventive behaviour (96). Similarly, e-Health and related diet-related applications are being increasingly used for professional 1 Department of Artificial Intelligence, Faculty of Computer Science and and personal purposes. People are using these applications to make healthier lifestyle choices. Generally, these apps provide instant nutritional values of food items with barcode scanners, which is extremely helpful for people suffering from non-communicable diseases, and others who intend to choose healthier products (1). These applications not only assist users with the selection of more nutritious alternatives but also allow them to self-monitor their physical activity and diet intake by using behavioural strategies of goal settings (6). Moreover, these applications are designed to cater to various age groups, including children battling obesity from a very young age.
In this regard, recent developments in artificial intelligence-based functionalities and hardware capacity enhancement of handheld devices have led to the development of automatic food recognition and calories estimation methods, making them an essential subset of e-health applications.
Regardless of numerous diet-related applications freely available today, scientifically proven guidelines (both in terms of usability and functionality) have not yet emerged from the users' and the dietitian's perspective. Also, the author's first-hand app development experience (7) suggested a dire need to have in-depth knowledge about the state-of-theart diet-related applications. To develop this understanding, the first step involves identifying key components relevant to existing diet-related applications, which are categorized in terms of general issues faced by dieticians and users, including user experience of both parties and functionalities required by each of them, respectively.
While the development of diet-related applications requires a significant amount of time and effort, general issues like their credibility remain a question. The term "Credibility" here refers to the authenticity or scientific validation of an application to achieve goal during trials. Another challenge present applications face is the maintenance of an updated food composition database, as new food products are being continuously introduced in the market. Mobile app developers also find it challenging to determine target users, their needs, and potential feedback to improve functionality and usability of apps (7) (8). Thus, an application with a good user experience may increase its preference over others despite offering lesser functionality. Therefore, the development of such applications should strongly consider essential factors like usability and 'ease of use' (9) (10), as poor usability can result in users switching over to alternative options (11) (7) (12).
The following paper aims to provide a review of existing diet-related applications and seeks to equip researchers and dietitians with comprehensive knowledge about general issues encountered by their users in terms of usability and functionality. Thereby laying the foundation for developing state-of-the-art generalized solutions that can cater to vastly varying user needs. Moreover, other fields in which evidence supports the effectiveness of digital interventions can learn a valuable lesson from the findings of this study.

Methods
We have developed the review protocol by defining our research questions and considering multiple inclusion/exclusion criteria. Then we formally defined our search strategy by identifying the search terms and carried out the search using the electronic database of PUBMED, CINAHIL, and Science Direct. Following this, we selected relevant studies based on our study selection criteria. Then we extracted the data and presented our results.

Research Questions
The primary aim of this review is to answer the research questions shown in Table 1.

Inclusion/Exclusion Criteria
The studies that met all of the following criteria are selected for this review. IC1. Papers related to dietary applications for smartphones (iPhones, Android phones, and Blackberries) and modern commercially available portable devices such as iPads and Personal Digital assistants (PDAs). IC2. Content is written in the English language only. IC3. The study must be a full peer-reviewed paper (not an abstract). IC4. Dates of Publication: PubMed and CINAHL: 1/1/10-31/12 /19, Science Direct: 2010 This review excludes the following studies that are conformed to at least one of the following criteria. EC1. Studies without a clear description of dietary application mentioned. EC2. Dietary applications that are not freely available.

Database Identification
We choose PubMed, CINAHL and Science Direct due to the following reasoning. PubMed database gives a publicly available search interface for MEDLINE and National Library of Medicine, which makes it one of the most widely accessible biomedical resources globally (89). Similarly, the CINAHL database provides allied health care literature, thus making it a good resource for literature related to mHealth applications (90). We selected Science Direct as it provides broad access to a database of scientific and medical research (91).

Search Strategy
We have carefully defined the search terms based on initial screening through a consensus among authors to investigate the diet-related mobile applications. Terms such as cellular

No
Research question Motivation RQ1 What are the general problems that are resolved by the freely available diet-related applications?
To provide information about the general problems faced by dietary assessment apps such as frequent app crashes (82), cumbersome process of entering meal information, demotivating information displays (50), periodic notifications, difficulty in portion size estimation (80), credibility (78, 84), etc.

RQ2
What are back-end application issues resolved by the freely available dietary applications?
To provide information about the application's stability, usage reports (104), data confidentiality (85), and offline accessibility-related issues faced by diet-related applications.

RQ3
To what extent do the freely available dietary applications fulfill user interface requirements?
To provide information regarding the critical user interface components (28,  Search targets the following keywords ("cellular phone" AND diet, "mobile phone" AND diet, smartphone AND diet, mHealth AND diet, iPads AND diet, "cellular phone" AND food, "mobile phone" AND food, smartphone AND food, mHealth AND food, iPads AND food, "cellular phone" AND nutrition, "mobile phone" AND nutrition, smartphone AND nutrition, mHealth AND nutrition, iPads AND nutrition ). The Boolean AND joins the two major parts. These yield 25950 results, reduced to 13,897 after duplicates removal. They are screened based on titles, and we accessed a total of 775 articles for eligibility against our inclusion/exclusion criteria and study selection process. We scanned references of eligible studies to identify additional studies, but we have not included additional studies in this review. Finally, we included a total of 56 studies in this review process. Table 2 shows the search terms and their corresponding search results. The PRISMA diagram in Figure 1 shows the search flow and inclusion/exclusion of studies.

Evaluation Criteria and Data Extraction
Reviewer GAT extracted all the selected studies' key characteristics (study population, location, mobile app details, and aim of the survey) shown in Table 3. Similarly, the Expert Group compromised of the authors of this manuscript identified the attributes of each research question shown in Table 4, 5, 6 and 7 that are mentioned in the existing literature of mHealth apps for data extraction to answer our  (50), the credibility of the database (78, 84) etc. Table S1 and S2 provide the extracted data of general issues in the supplementary material. We extracted the data regarding stability of the application (82), usage reports (104), data confidentiality (85) and offline accessibility (105) for back-end application issues. Table S3 provides the extracted data in the supplementary material. For user interface requirements (28,(74)(75)(76)(77), we extracted data of the attributes mentioned in Table 6. Table S4 and S5 in the supplementary material provides the extracted data. Under the heading of dietary components (78, 84), we extracted the details of the attributes shown in Table 7. Table S6 and S7 in the supplementary material provides the extracted data. We carried out the whole process by completing the data extraction forms. Two researchers verified the data's soundness and ensured data extracted from each study justified the study's aim. When the publications identified in the searches did not provide sufficient detail of mHealth apps, additional literature, websites, contacts with authors, or application use itself was used to fill gaps.

Results
This section presents the results of the essential characteristics of each selected study. It shows the results obtained from the extracted information to answer our research question. The brief detail of all the data extracted to answer our research question is provided in the study's supplementary material.

Study Selection
The

RQ1
: What are the general problems that are resolved by the freely available diet-related applications?
To determine the general issues found in existing applications, we have categorized important parameters from different perspectives of users and dietitians as shown in Figure 2. For this purpose, we surveyed 35 freely available mHealth apps from included studies.
These general issues mentioned by dietitians and users in existing mHealth apps include credibility, (78) localization of database sources, (80), and difficulty in portion size estimation (79). Moreover, applications that require users to go through multiple steps for data entry (81) make the process cumbersome and negatively impact the whole user experience. (Figure 3) (A) shows the percentage breakdown of applications that looked to resolve these issues.
Subsequently, portion size estimation also plays a vital role when it comes to dietary applications. This component usually requires prior contextual knowledge to ensure better accuracy. Several apps deal with fixed food measurements in terms of serving size, weight, or other simple household measurements. Generally, it is hard for most people to convert what they see on their plates to these measurements for entering into dietary apps. Moreover, when it comes to Asian food, estimating portion size becomes even more challenging when multiple food items are mixed or placed on top of each other. Therefore, over or underestimating portion size is common for unskilled individuals, even more so in Asian families where each meal consists of multiple side dishes. These challenges make the estimation of portion size a complicated task for machine learning researchers, application developers, and dietitians. Many existing applications (6, 20, 22, 27-29, 32, 34, 35, 48, 66-68) do not accommodate features which support estimation of portion size. Alternately, many existing applications (15, 17-20, 22, 27-29, 32-34, 36, 37, 41, 45, 54, 55, 59, 60, 62, 65-70) require minimum steps for data recording ensuring a smooth user experience.
General issues faced by users involve frequent app crashes (82), cumbersome process of entering meal details, demotivating information displays, dependence on expensive electrical devices such as fit bands (50), frequent notifications and difficulty in estimating portion size (80). As shown in figure 3 (B), out of 35 surveyed applications, 6 applications (41,42,44,45,69,70) had no information about application's stability in terms of app crashes. Both "happy" (17) and "lose it" (18) experienced frequent app crashes. The remaining applications do not experience frequent app crashes.
Furthermore, large number of surveyed applications display motivating information and require less steps to record user information (15, 17-22, 27-29, 32-37, 41, 54, 55,  . Frequent notifications often bother the user; especially when the app provides notifications after nearly every step. Also, 40% of surveyed applications had no information available about notification or reminder settings, (6,20,24,27,31,32,35,36,42,44,48,60,68,70) whereas remaining applications accommodated notification system except "lose it" (18). Furthermore, all applications except FoodWiz2 (62) and MyFitness Pal (Log2Lose) (67) do not require any sort of electrical device. Also, almost 37% of applications (19) (48) failed to address the cumbersome process of entering meal information. In addition to this, a large number of existing applications do not address the difficulty in portion size estimation. This is due to multidimensional challenges, from users' perspective; as it is difficult to estimate the portion size of food items used during preparation of food at different restaurants. Moreover, lack of guidance/reference regarding the quantity, further complicates the procedure of estimating portion size.
RQ2: What are back-end application issues resolved by the freely available dietary applications?
The backend is an essential part of any mobile application, as it involves data storage, business logic, and security. Therefore, it plays the role of a server for mobile applications and stores information invisible to the end-users. Figure  4 presents backend application issues faced by end-users. Backend issues generally involve no offline access to the key features (105), absence of usage reports (104), privacy or data confidentiality concerns (85), and frequent application crashes (82). Therefore, the issues mentioned above should be addressed by mobile applications to enhance the usability or user-friendliness of any diet-related application. Reduced dependence on the Internet will not only improve usability. It will also enhance the app's responsiveness and data processing, as the end-user is not restricted from recording their data offline. Thus far, only 3 out of 35 surveyed applications allow offline accessibility (22) (41) (67), whereas other applications require an internet connection for data transmission to their respected servers. Moreover, apps like Diet Cam rely on the client-server configuration for connectivity between mobile phones and databases (21), which again requires a stable internet connection. Many of the applications surveyed suffer from technical glitches and slow processing speed due to their dependence on a reliable internet connection. Therefore, offline accessibility can help to address all these concerns.
Another important issue is lack of data confidentiality and privacy. Mobile applications, especially health-related applications, should have concrete measures to ensure user's records' confidentiality. Similarly, web services included in mobile applications should extract data without any leakages and minimal pilferage instances. Almost 22% of surveyed applications offer data privacy, while many studies do not mention this problem. Moreover, some existing applications such as Social POD (15), Happy (17), and 'mDPP' (19) report user engagement or adherence to the app declined over time. Figure 5 describes percentage of applications that managed to resolve aforementioned issues.
RQ3: To what extent do the freely available dietary applications fulfill user interface requirements?
Generally, user interface requirements encompass application design, user-friendliness, tutorial page, and two-user dashboard. As application design is one of the main requirements (28,76,77), as it should be simple, have nice and appropriate icons along with clear font size and color to improve usability. Out of 35 surveyed applications, 29 applications met the design criteria according to users' requirements. However, remaining applications (15,19,29,35,37,48) did not endorse their design details. Another feature which enhances usability is the presence of appropriate tutorial pages (74, 75). For many dietrelated applications, tutorial pages are preferred to show the metric measurements of serving size of food for a better understanding of the user. Unfortunately, most of the surveyed apps fail to provide this information, and only 20% of surveyed applications (20,22,45,55,64,67,69) were able to provide the details for a tutorial page.
Two-user dashboards are another essential feature whereby a simplified or easy-to-use version of the dashboard is available for patients or the general public. A more detailed version is available for dietitians or researchers. Most surveyed applications do not incorporate this feature except for the Dietary Intake Assessment app (47).
User interface requirements also involve information to include in the user profile, and notification alerts to the user (76). Besides basic information, the application should allow users to set goals in terms of desired body weight, and diet (76, 78). Only 53% of surveyed applications (15,18,23,28,30,33,35,69) included goal-setting feature, while others did not even provide personalized profiles.
Finally, another important feature of diet-related applications is notification alert to users (78). Reminders assist users in punching in their updated information and updating their body weight regularly in the app, thereby keeping track of their progress. Similarly, alerts to consume meals at specified times, alerts for calories, drinking water, and doing exercises improve user engagement. 62% of total surveyed applications (6, 16, 18-20, 23, 29, 32, 33, 35, 37, 41, 44, 45, 48, 69) were found out to provide such alerts to their users. Figure 6 shows the percentage of existing applications that are implementing these features.

RQ4: What are the dietary components and critical features implemented by the freely available dietary applications?
Dietary component functionality mainly included evaluation of diet quality, options to add supplements to the diet, history tracking, and storage of these records. Other essential features include validity and comprehensiveness of database (78, 84), portion size estimation (79) and diet/nutrient summary that provides information in terms of calories for each meal as show in Figure 7. Figure 8 below illustrates the summary of the results gathered from surveyed applications. To provide a good evaluation of diet quality, a dietary app should display macronutrients' balance and include reference values for interpretation. Based on this information, 34 out of 35 surveyed applications were able to assess diet quality properly.
Moreover, options to track users' weekly diet records and their storage on websites for later use are considered important factors that can improve user experience. As per our survey total 26 applications (6, 15, 17, 18, 20-22, 28, 29, 31, 32, 36, 44, 45, 48, 54, 55, 59, 60, 64, 65, 67-69) facilitate users by giving them access to their previous records. Items included in existing applications should also be considered an essential feature, as some applications are particular about specific food items (like beverages). In contrast, other diet apps provide users with options to customize the food choices accordingly.
As for the nutrient summary, most application databases include calorie information while other surveyed applications provide more specific nutrient information in databases. Apps like "Lose it" (18) provide information about three significant macronutrients like carbohydrates, proteins, and fats, which guide users to make better food choices.
To enhance the user-friendliness of an application, tailored messages, feedback, and notifications according to user dietary intake (76) are essential factors to be considered. Acting as guidelines for users, they improve the userfriendliness and user experience of an application. For instance, apps like My Meal Mate (6), 'iDAT' (32), and MyFitnessPal (22) display remaining calorie allowance to guide the user to achieve dietary goals.
Furthermore, applications can make use of visual aids by providing summaries of energy and nutrients intake in the form of a diary, pie chart, table, and progress bar (77) for better comprehension. Applications such as ENGAGED (34), provide goal thermometers to display user goals and the actual amount of calories and fat (in grams) consumed.
Finally, we have ranked these applications based on the number of features they have implemented and mentioned in their study. Lark application, Food wiz2, Gocarb application had a higher score in fulfilling the number of requirements from dietitians' or researchers' reference frames. On the other hand, MyFitnessPal, Engaged, and MyFoodApp focuses more on the general population's requirements. Figure 10 and Figure 9 show the applications score.   . Application score by keeping in view requirements from dietician perspective.Equal weight is given to each category and applications fulfilling more requirements have the highest score. The maximum total score is 4, and the max score of each category is one. Figure 10. Application score by keeping in view requirements from user perspective.Equal weight is given to each category and applications fulfilling more requirements have the highest score. The maximum total score is 4, and the max score of each category is one.

RQ5: What are the benefits and challenges stemming from the included case studies?
Current case studies have several benefits that can help users monitor their daily diet and help them resolve diet-related issues. Based on the shortlisted studies, we investigated freely available diet-related applications in terms of features, general problems, and usability challenges. Our findings aim to provide a broader view of current solutions to dietitians, health experts, and researchers alike. Overall, the case studies equip both general users and health experts with information on the critical features that are not catered by most of the existing diet-related apps. Moreover, they will help users quickly determine the viability of existing solutions to recommend further or use the solution that fulfills their needs in the best possible way. Thus, these studies have paved the way for the research community to introduce standard guidelines for future diet-related apps according to criteria. As a result, the apps will be more substantial for patients, general users, and dietitians.
Apart from this, the studies also highlight different challenges that can undermine current applications' actual purpose. Major obstacles include integration and updating large food databases as food recipes, and their nutrient content varies from region to region. In addition to this, new food items are being introduced in the market every day. Therefore, making the design and implementation of such systems a difficult task. Similarly, a database's comprehensiveness is one of the primary requisites of users to keep track of their micronutrients and macronutrients. Other than this, the incorporation of user-friendliness along with notifications and personalized alerts are the challenges that the research community should consider. Also, data security is of vital importance (85) due to strict policies of regulating authorities and rising public concerns over sharing private data. Therefore, diet-related apps should ensure data privacy and confidentiality, which, unfortunately, many surveyed apps fail to address.

Discussion
We initiated this evaluation because of the rapid recent emergence of freely available diet-related apps coupled with increasing concerns over general issues, usability challenges and missingness of critical features. Following that, we investigated the strength and weaknesses of freely available diet-related apps. The primary emphasis of previous reviews by Rusin et al. We focused on mHealth apps identified from existing publications between 2010-2019. After carrying out the literature search on three scientific databases, we evaluated 35 mHealth applications based on their usability, critical features and shows their strengths and weaknesses. The user-friendliness and high engagement are of considerable importance (77), especially since 68% of the existing mHealth apps incorporate this feature. We recommend that user's input in the development of mHealth interventions and other considerations for end-users should be sought early on in the process of app or digital health intervention design to ensure long and short term engagement (100) (101) (102)  (103). Similarly, the user notifications are equally important, as it keeps them engaged and motivated (78). According to the survey, we found that 62% of the apps provides timely alerts to the user. Likewise, goal setting also holds critical significance, as it gives information about user's personal preferences required for modification of their behaviour accordingly (76, 78). Therefore, about 53% of the surveyed applications include the goal settings feature.
Likewise, our findings indicate that existing applications are lagging in various aspects. Despite the importance of the credibility of database resources (78), only 30% of surveyed applications highlighted this issue. Besides credibility, the comprehensive validation of the database with detailed information on macronutrients and micronutrients is also essential for clinical use. However, only 37% of the applications have included validated databases. Despite the rise of artificial intelligence, the methods for estimating portion size and logging food photos from the camera have made significant advancements (38,51), many apps still depend on household measurements for portion size estimation or manual entries of the food log.
Due to rising concerns of data security among users (85), diet-related apps must encrypt user data and use standardized protocols to ensure data privacy and confidentiality. Yet, the results indicate that only 22% of surveyed applications have addressed data privacy issues. Similarly, there is a lack of economic data in existing studies to support using mHealth apps for dietary assessment. Although the economic evaluation of mHealth apps is necessary to provide an evidence-based assessment of sustainability and benefits of investing in such technologies. (98) (99).
Despite considerations that existing diet-related apps should address, all of the studies are valuable to broaden the research community's knowledge. The identified applications in these works serve as a guide for users to choose between healthier alternatives and improve their dietary habits in the long term.
Finally, we have made the following recommendations for the research community based on our study. A localized database is essential for nutritional assessment apps due to variations in the food recipes and diet preferences among different cultures. Future diet-related apps should also consider the technological advancement in artificial intelligence and explore the current methods of logging food and automated portion size estimation from food photos.
It is noteworthy that several studies have implemented AIbased strategies, but further investigation of these methods is required on a large scale. Furthermore, there is a dire need to develop standard guidelines for the development of diet-related apps, as standardized solutions will be more reliable in the future for patients, general users, and dietitians. Finally, when designing modern diet-related applications, the research community should consider our findings to enhance the usability and completeness of the solution.

Limitations of the data gathered for this study
This review has limitations that require further investigations. Firstly, the analysis was limited to studies published in the searched databases and only written in the English language. Related articles in other languages were not included. Secondly, this research does not consider demographic information about a particular race or culture while designing the research questions.

Conclusion
Dietary apps for nutritional assessment are developed to assist users with their diet-related issues or keep track of their dietary intake. Such apps tend to act as guides and enable users to choose healthier alternatives to improve their nutritional habits in the long term. Therefore, due to the vital importance of diet-related apps, this SLR analyzed a wide range of existing literature on mHealth apps from scientific databases of CINAHL, Science Direct, and PUBMED and shortlisted almost 56 studies. We have investigated the apps' comprehensiveness in terms of critical features, general issues, and usability challenges from general users' reference frames. We have further examined the strength and weaknesses of the existing freely available dietrelated apps and summarized concerns and gaps for future work. Our findings show that the credibility of database resources, comprehensive information about macronutrients and micronutrients, validation of database, data privacy, use of AI for food logs, and automated portion size estimation from the pictures are foremost challenges. Addressing the challenges mentioned above will improve the usability and comprehensiveness of diet-related apps. Therefore, making them more substantial for patients, general users, and dieticians. Moreover, implementing blockchain technology and health standards for data security, exploring recent trends in continual learning for food recognition, and outlining standard guidelines for regulating apps are essential future topics that can be explored.     To accurately measure food and nutrient intake by use of image processing methods.
Continued on next page  Determine smartphone apps' effectiveness for weight loss programs by giving financial rewards and dietary self-monitoring.