Is a Picture Worth a Thousand Words? Few Evidence-Based Features of Dietary Interventions Included in Photo Diet Tracking Mobile Apps for Weight Loss

Validation of the SmartPlate for detecting food weight and type

This study determined accuracy (comparing to criterion), inter-plate reliability (comparing measures between two plates), and intra-plate reliability (comparing successive measures on one plate) of the SmartPlate for food weight and type. Food weight validation included comparing SmartPlate weights to criterion [reference] scale weights (1,980 measures) and weights of 188 foods (2,256 measures). Food type validation included assessing SmartPlate accuracy for 188 foods. For weight, mean absolute percent errors for accuracy, inter-plate reliability, and intra-plate reliability were 6.2, 7.4, and 4.9%, respectively. For food type, foods were correctly identified/listed or searchable 67.0 or 98.9% of the time, respectively, with 76.0% inter-plate reliability and 86.3% intra-plate reliability. The SmartPlate had acceptable accuracy and reliability for assessing food weight and type and may be appealing for monitoring dietary surveillance or intervention. Due to high intra-plate reliability, the SmartPlate may be especially useful for one-on-one interventions and assessing change over time.

MyDietCam: Development and usability study of a food recognition integrated dietary monitoring smartphone application

Background

Diet monitoring has been linked with improved eating habits and positive health outcomes such as prevention of obesity. However, this is often unsustainable as traditional methods place a high burden on both participants and researchers through pen and paper recordings and manual nutrient coding respectively. The digitisation of dietary monitoring has greatly reduced these barriers. This paper proposes a diet application with a novel food recognition feature with a usability study conducted in the real world.

Methods

This study describes the development of a mobile diet application (MyDietCam) targeted at healthy Malaysian adults. Focus group discussions (FGD) were carried out among dietitians and potential users to determine ideal features in a diet application. Thirty participants were recruited from a local university to log their meals through MyDietCam for six days and submit the Malay mHealth Application Usability Questionnaire (M-MAUQ) at the end of the study.

Results

The findings from the FGD led to the implementation of the main features: individualised recommendations, food logging through food recognition to reduce steps for data entry and provide detailed nutrient analyses through visuals. An average overall usability score of 5.13 out of a maximum of seven was reported from the M-MAUQ which is considered acceptable.

Conclusion

The development of a local (Malaysian) mobile diet application with acceptable usability may be helpful in sustaining the diet monitoring habit to improve health outcomes. Future work should focus on improving the issues raised before testing the effectiveness of the application for improving health outcomes.

Using FIGO Nutrition Checklist counselling in pregnancy: A review to support healthcare professionals

The period before and during pregnancy is increasingly recognized as an important stage for addressing malnutrition. This can help to reduce the risk of noncommunicable diseases in mothers and passage of risk to their infants. The FIGO Nutrition Checklist is a tool designed to address these issues. The checklist contains questions on specific dietary requirements, body mass index, diet quality, and micronutrients. Through answering these questions, awareness is generated, potential risks are identified, and information is collected that can inform health-promoting conversations between women and their healthcare professionals. The tool can be used across a range of health settings, regions, and life stages. The aim of this review is to summarize nutritional recommendations related to the FIGO Nutrition Checklist to support healthcare providers using it in practice. Included is a selection of global dietary recommendations for each of the components of the checklist and practical insights from countries that have used it. Implementation of the FIGO Nutrition Checklist will help identify potential nutritional deficiencies in women so that they can be addressed by healthcare providers. This has potential longstanding benefits for mothers and their children, across generations.

Should you "picture" this? Effects of picture-taking features of food diary apps on memory, liking, and wanting

Picture-taking functions are commonly available features in food diaries and other mobile applications that may influence how we think about the very food we consume. Because memories of food (Higgs & Donohoe, 2011) and the act of recording food consumption (Turk et al., 2013) have been shown to influence desire for and consumption of food, this paper investigated the effects of using the picture-taking feature of a food diary app on liking, wanting, and memory of food. Using a simple food diary app with a picture-taking feature loaded onto iPads, participants took part in a lab experiment where they either did or did not use the picture-taking feature of the app as they ate a snack. To capture the changes in liking and wanting that naturally occur as more food is consumed, participants were also randomly assigned to receive either larger or smaller portions of the snack. The results indicate that picture-taking while eating is associated with greater wanting of the food following consumption. Furthermore, for smaller portions of food, taking pictures during consumption is associated with greater liking of the food. However, taking pictures in the smaller portion size condition was also associated with less detailed recall of food's sensory properties.

Patient Use of Cardiovascular Devices and Apps: Are We Getting Our Money's Worth?

The evolution of technology makes it likely that a large number of people will invest in and use health-related mobile applications and wearable devices. Yet the question remains: Do these technology-based interventions modify health behavior and improve health…and are we getting our money's worth? The vast majority of studies concerning health-related apps and wearable devices have small sample sizes and short time spans of 6 months or less, so it is not clear if these durations were determined by lack of consistent use over time. Furthermore, many of the most popular applications have not been subjected to randomized trials. Overall, the small demonstrated improvements in outcomes are often associated with professional involvement from clinicians, coaches, or diabetes educators provided in conjunction with use of mobile health (mHealth) platforms. This paper explores the use of mHealth technologies that address cardiovascular disease/prevention (eg, diabetes, diet, physical activity, and associated weight loss) and discusses the lack of adequate evidence to support even minimal patient investment in mobile applications or wearable devices at this time.

The landscape of nutri-informatics: a review of current resources and challenges for integrative nutrition research

Informatics has become an essential component of research in the past few decades, capitalizing on the efficiency and power of computation to improve the knowledge gained from increasing quantities and types of data. While other fields of research such as genomics are well represented in informatics resources, nutrition remains underrepresented. Nutrition is one of the most integral components of human life, and it impacts individuals far beyond just nutrient provisions. For example, nutrition plays a role in cultural practices, interpersonal relationships and body image. Despite this, integrated computational investigations have been limited due to challenges within nutrition informatics (nutri-informatics) and nutrition data. The purpose of this review is to describe the landscape of nutri-informatics resources available for use in computational nutrition research and clinical utilization. In particular, we will focus on the application of biomedical ontologies and their potential to improve the standardization and interoperability of nutrition terminologies and relationships between nutrition and other biomedical disciplines such as disease and phenomics. Additionally, we will highlight challenges currently faced by the nutri-informatics community including experimental design, data aggregation and the roles scientific journals and primary nutrition researchers play in facilitating data reuse and successful computational research. Finally, we will conclude with a call to action to create and follow community standards regarding standardization of language, documentation specifications and requirements for data reuse. With the continued movement toward community standards of this kind, the entire nutrition research community can transition toward greater usage of Findability, Accessibility, Interoperability and Reusability principles and in turn more transparent science.

Impact on Dietary Intake of Two Levels of Technology-Assisted Personalized Nutrition: A Randomized Trial

Advances in web and mobile technologies have created efficiencies relating to collection, analysis and interpretation of dietary intake data. This study compared the impact of two levels of nutrition support: (1) low personalization, comprising a web-based personalized nutrition feedback report generated using the Australian Eating Survey® (AES) food frequency questionnaire data; and (2) high personalization, involving structured video calls with a dietitian using the AES report plus dietary self-monitoring with text message feedback. Intake was measured at baseline and 12 weeks using the AES and diet quality using the Australian Recommended Food Score (ARFS). Fifty participants (aged 39.2 ± 12.5 years; Body Mass Index 26.4 ± 6.0 kg/m2; 86.0% female) completed baseline measures. Significant (p < 0.05) between-group differences in dietary changes favored the high personalization group for total ARFS (5.6 points (95% CI 1.3 to 10.0)) and ARFS sub-scales of meat (0.9 points (0.4 to 1.6)), vegetarian alternatives (0.8 points (0.1 to 1.4)), and dairy (1.3 points (0.3 to 2.3)). Additional significant changes in favor of the high personalization group occurred for proportion of energy intake derived from energy-dense, nutrient-poor foods (-7.2% (-13.8% to -0.5%)) and takeaway foods sub-group (-3.4% (-6.5% to 0.3%). Significant within-group changes were observed for 12 dietary variables in the high personalization group vs one variable for low personalization. A higher level of personalized support combining the AES report with one-on-one dietitian video calls and dietary self-monitoring resulted in greater dietary change compared to the AES report alone. These findings suggest nutrition-related web and mobile technologies in combination with personalized dietitian delivered advice have a greater impact compared to when used alone.

Nutrition-Related Mobile Apps in the China App Store: Assessment of Functionality and Quality

BACKGROUND

There are an increasing number of mobile apps that provide dietary guidance to support a healthy lifestyle and disease management. However, the characteristics of these nutrition-related apps are not well analyzed.

OBJECTIVE

This study aimed to evaluate the functionality and quality of nutrition-related apps in China.

METHODS

Mobile apps providing dietary guidance were screened in the Chinese iOS and Android app stores in November 2017, using stepwise searching criteria. The first screening consisted of extracting information from the app descriptions. Apps that (1) were free, (2) contain information on diet and nutrition, and (3) were last updated after January 1, 2016, were downloaded for further analysis. Nutritional functionalities were determined according to the Chinese Dietary Guidelines framework. Market-related functionalities were developed from previous studies and tailored to downloaded apps. The quality of apps was assessed with the user version of the Mobile App Rating Scale (uMARS).

RESULTS

Out of 628 dietary guidance apps screened, 44 were nutrition-related. Of these, guidance was provided on diet exclusively (11/44, 25%), fitness (17/44, 39%), disease management (11/44, 25%), or maternal health (5/44, 11%). Nutritional functionalities included nutritional information inquiry (40/44, 91%), nutrition education (35/44, 80%), food record (34/44, 77%), diet analysis (34/44, 77%), and personalized recipes (21/44, 48%). Dietary analysis and suggestions mainly focused on energy intake (33/44, 75%) and less on other factors such as dietary structure (10/44, 23%). Social communication functionalities were available in 42 apps (96%), user incentives were supported in 26 apps (59%), and intelligent recognition technology was available in 8 apps (18%). The median score for the quality of the 44 apps, as determined on a 5-point uMARS scale, was 3.6 (interquartile range 0.7).

CONCLUSIONS

Most nutrition-related apps are developed for health management rather than for dietary guidance exclusively. Although basic principles of energy balance are used, their nutritional functionality was relatively limited and not individualized. More efforts should be made to develop nutrition-related apps with evidence-based nutritional knowledge, comprehensive and personalized dietary guidance, and innovative technology.

OneNote Meal: A Photo-Based Diary Study for Reflective Meal Tracking

When a self-monitoring tool is used to enhance behavior awareness, the tool should afford reflection by design. This work examines the "valence of meal" (i.e., healthy versus unhealthy meal) as a means to support reflection on a person's diet in photo-based meal tracking. To study the effect of imposing valence on meal tracking, we designed two conditions-one focusing on capturing healthy meals, the other capturing unhealthy meals-and conducted a between-subjects diary study with 22 college students over four weeks. According to their group assignment, participants tracked only healthy or unhealthy meals by taking photos and rationalizing in texts why their meals were particularly healthy or unhealthy. We found that participants in both groups became more aware of their diet, but the valence of meal influenced them differently regarding their meal assessment, self-reflection, and food choice intention. We discuss ways to leverage valence in designing reflective meal tracking systems.

User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research

BACKGROUND

The need for a better understanding of food consumption behaviour within its behavioural context has sparked the interest of nutrition researchers for user-documented food consumption data collected outside the research context using publicly available nutrition apps. The study aims to characterize the scientific, technical, legal and ethical features of this data in order to identify the opportunities and challenges associated with using this data for nutrition research.

METHOD

A search for apps collecting food consumption data was conducted in October 2016 against UK Google Play and iTunes storefronts. 176 apps were selected based on user ratings and English language support. Publicly available information from the app stores and app-related websites was investigated and relevant data extracted and summarized. Our focus was on characteristics related to scientific relevance, data management and legal and ethical governance of user-documented food consumption data.

RESULTS

Food diaries are the most common form of data collection, allowing for multiple inputs including generic food items, packaged products, or images. Standards and procedures for compiling food databases used for estimating energy and nutrient intakes remain largely undisclosed. Food consumption data is interlinked with various types of contextual data related to behavioural motivation, physical activity, health, and fitness. While exchange of data between apps is common practise, the majority of apps lack technical documentation regarding data export. There is a similar lack of documentation regarding the implemented terms of use and privacy policies. While users are usually the owners of their data, vendors are granted irrevocable and royalty free licenses to commercially exploit the data.

CONCLUSION

Due to its magnitude, diversity, and interconnectedness, user-documented food consumption data offers promising opportunities for a better understanding of habitual food consumption behaviour and its determinants. Non-standardized or non-documented food data compilation procedures, data exchange protocols and formats, terms of use and privacy statements, however, limit possibilities to integrate, process and share user-documented food consumption data. An ongoing research effort is required, to keep pace with the technical advancements of food consumption apps, their evolving data networks and the legal and ethical regulations related to protecting app users and their personal data.

The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges

OBJECTIVE

MyFitnessPal is the most popular commercial nutrition weight loss app. The aim of this study was to assess how individuals in naturalistic settings performed when recording their dietary intake in MyFitnessPal, and their usability experiences with the app.

METHODS

Adults not regularly using MyFitnessPal (N = 43) logged their dietary intake in the app for 4 consecutive days and completed two researcher-administered 24-h recalls collected based on the Automated Multiple Pass Method. Food items from 24-h recalls were coded into food categories and foods omitted from corresponding MyFitnessPal records were calculated. Comparative validity of energy and macronutrient outputs from MyFitnessPal were compared against 24-h recalls using paired t tests. Inductive thematic analysis was applied to app usability responses.

RESULTS

Individuals omitted a mean of 18% (SD, 15) of food items, particularly energy-dense and nutrient-poor foods from MyFitnessPal records. Relative to 2-day 24-h recalls, 4-day MyFitnessPal records significantly underestimated mean energy intake by 1863 kJ (SD, 2952 kJ, P = 0.0002) and intake of all macronutrients. Although 80% of participants rated MyFitnessPal as easy to use, only 20% said they would continue use, citing challenges in matching foods, estimating portion size, and logging being time-consuming, as affecting motivation for long-term use.

CONCLUSIONS

Large discrepancies in nutrient measurements from MyFitnessPal indicate suboptimal performance with using the app to record intake, particularly given food omissions in records and difficulties encountered with app usability relating to the food database and input of portion sizes. Stand-alone use of MyFitnessPal is therefore cautioned and guidance from dietitians is necessary to support use of nutrition apps in collecting accurate dietary data.

Smartphone apps and the nutrition care process: Current perspectives and future considerations

OBJECTIVE

To provide dietitians with practical guidance on incorporating smartphone applications (apps) in the nutrition care process (NCP) to optimize patient education and counseling.

METHODS

The current evidence-base for mobile health (mHealth) apps was searched using PubMed and Google Scholar. Where and how apps could be implemented by dietitians across the four steps of the NCP is discussed.

RESULTS

With functionality to automatically convert patient dietary records into nutrient components, nutrition assessment can be streamlined using nutrition apps, allowing more time for dietitians to deliver education and nutrition counseling. Dietitians could prescribe apps to provide patients with education on nutrition skills and in counseling for better adherence to behavior change. Improved patient-provider communication is also made possible through the opportunity for real-time monitoring and evaluation of patient progress via apps. A practical framework termed the 'Mobile Nutrition Care Process Grid' provides dietitians with best-practice guidance on how to use apps.

CONCLUSIONS

Including apps into dietetic practice could enhance the efficiency and quality of nutrition care and counseling delivered by dietitians.

PRACTICE IMPLICATIONS

Apps should be considered an adjunct to enable dietetic counseling and care, rather than to replace the expertise, social support and accountability provided by dietitians.

Erratum: The Dietary Intervention to Enhance Tracking with Mobile Devices (DIET Mobile) Study: A 6-Month Randomized Weight Loss Trial

OBJECTIVE:

To examine the use of two different mobile dietary self-monitoring methods for weight loss.

METHODS:

Adults with overweight (n = 81; mean BMI 34.7 ± 5.6 kg/m²) were randomized to self-monitor their diet with a mobile app (App, n = 42) or wearable Bite Counter device (Bite, n = 39). Both groups received the same behavioral weight loss information via twice-weekly podcasts. Weight, physical activity (International Physical Activity Questionnaire), and energy intake (two dietary recalls) were assessed at 0, 3, and 6 months.

RESULTS:

At 6 months, 75% of participants completed the trial. The App group lost significantly more weight (−6.8 ± 0.8 kg) than the Bite group (−3.0 ± 0.8 kg; group × time interaction: P < 0.001). Changes in energy intake (kcal/d) (−621 ± 157 App, −456 ± 167 Bite; P = 0.47) or number of days diet was tracked (90.7 ± 9.1 App, 68.4 ± 9.8 Bite; P = 0.09) did not differ between groups, but the Bite group had significant increases in physical activity metabolic equivalents (+2015.4 ± 684.6 min/wk; P = 0.02) compared to little change in the App group (−136.5 ± 630.6; P = 0.02). Total weight loss was significantly correlated with number of podcasts downloaded (r = −0.33, P < 0.01) and number of days diet was tracked (r = −0.33, P < 0.01).

CONCLUSIONS:

While frequency of diet tracking was similar between the App and Bite groups, there was greater weight loss observed in the App group.

Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus

Cardiovascular disease is the leading cause of morbidity and mortality globally, with diabetes being an independent risk factor. Adequate diabetes management has proven to be resource-intensive, requiring frequent lab work, primary care and specialist visits, and time-consuming record-keeping by the patient and care team. New mobile health (mHealth) technologies have enhanced how diabetes is managed and care is delivered. While more recent work has investigated mHealth devices as complementary tools in behavioral interventions for diabetes prevention and management, little is still known about the effectiveness of mHealth technology as stand-alone intervention tools for reducing diabetes risk. In addition, more work is needed to identify the role of mHealth technology in treating vulnerable populations to ameliorate cardiovascular health disparities. With advances in mobile health technology development for diabetes prevention and management, these modalities will likely play an increasingly prominent role in reducing cardiometabolic risk for the US population.

Technology Interventions to Manage Food Intake: Where Are We Now?

PURPOSE OF REVIEW

This review describes the state-of-the-art for dietary assessment using smartphone apps and digital technology and provides an update on the efficacy of technology-mediated interventions for dietary change.

RECENT FINDINGS

Technology has progressed from apps requiring entry of foods consumed, to digital imaging to provide food intake data. However, these methods rely on patients being active in data collection. The automated estimation of the volume and composition of every meal consumed globally is years away. The use of text messaging, apps, social media, and combinations of these for interventions is growing and proving effective for type 2 diabetes mellitus (T2DM). Effectiveness of text messaging for obesity management is improving and multicomponent interventions show promise. A stand-alone app is less likely to produce positive outcomes and social media is relatively unexplored. A concentrated effort will be needed to progress digital dietary assessment. Researcher-designed technology programs are producing positive outcomes for T2DM but further research is needed in the area of weight management.

The Dietary Intervention to Enhance Tracking with Mobile Devices (DIET Mobile) Study: A 6-Month Randomized Weight Loss Trial

OBJECTIVE

To examine the use of two different mobile dietary self-monitoring methods for weight loss.

METHODS

Adults with overweight (n = 81; mean BMI 34.7 ± 5.6 kg/m² ) were randomized to self-monitor their diet with a mobile app (App, n = 42) or wearable Bite Counter device (Bite, n = 39). Both groups received the same behavioral weight loss information via twice-weekly podcasts. Weight, physical activity (International Physical Activity Questionnaire), and energy intake (two dietary recalls) were assessed at 0, 3, and 6 months.

RESULTS

At 6 months, 75% of participants completed the trial. The App group lost significantly more weight (-6.8 ± 0.8 kg) than the Bite group (-3.0 ± 0.8 kg; group × time interaction: P < 0.001). Changes in energy intake (kcal/d) (-621 ± 157 App, -456 ± 167 Bite; P = 0.47) or number of days diet was tracked (90.7 ± 9.1 App, 68.4 ± 9.8 Bite; P = 0.09) did not differ between groups, but the Bite group had significant increases in physical activity metabolic equivalents (+2015.4 ± 684.6 min/wk; P = 0.02) compared to little change in the App group (-136.5 ± 630.6; P = 0.02). Total weight loss was significantly correlated with number of podcasts downloaded (r = -0.33, P < 0.01) and number of days diet was tracked (r = -0.33, P < 0.01).

CONCLUSIONS

While frequency of diet tracking was similar between the App and Bite groups, there was greater weight loss observed in the App group.