Accuracy of applications to monitor food intake: Evaluation by comparison with 3-d food diary

Evaluating the Quality and Comparative Validity of Manual Food Logging and Artificial Intelligence-Enabled Food Image Recognition in Apps for Nutrition Care

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps' features, quality, behaviour change potential, and comparative validity of dietary assessment via manual logging and AI. The top 200 free and paid nutrition-related apps from Australia's Apple App and Google Play stores were screened (n = 800). Apps were assessed using MARS (quality) and ABACUS (behaviour change potential). Nutritional outputs from manual food logging and AI-enabled food-image recognition apps were compared with food records for Western, Asian, and Recommended diets. Among 18 apps, Noom scored highest on MARS (mean = 4.44) and ABACUS (21/21). From 16 manual food-logging apps, energy was overestimated for Western (mean: 1040 kJ) but underestimated for Asian (mean: -1520 kJ) diets. MyFitnessPal and Fastic had the highest accuracy (97% and 92%, respectively) out of seven AI-enabled food image recognition apps. Apps with more AI integration demonstrated better functionality, but automatic energy estimations from AI-enabled food image recognition were inaccurate. To enhance the integration of apps into nutrition care, collaborating with dietitians is essential for improving their credibility and comparative validity by expanding food databases. Moreover, training AI models are needed to improve AI-enabled food recognition, especially for mixed dishes and culturally diverse foods.

Effect of Peanut Butter Intake on Sleep Health in Firefighters: A Randomized Controlled Trial

Sleep is often impaired in firefighters due to the psychologically and physiologically intense nature of their work and working shift schedules. Peanut butter is affordable and a substantial source of monounsaturated fatty acids, which may aid sleep health. Thus, this study sought to determine if a daily serving of peanut butter consumed before bedtime for seven weeks altered sleep quality and quantity among full-time firefighters. Forty firefighters (peanut butter group = 20; control group = 20) participated in this eight-week randomized controlled trial. All participants completed a subjective questionnaire on mood, focus, and alertness twice daily and wore an Actigraph wristwatch to measure sleep variables, including latency, efficiency, time in bed, time asleep, wake after sleep onset, number of awakenings, and time spent awake. After a baseline week, the peanut butter group consumed two tablespoons of peanut butter two hours prior to bedtime for seven weeks. Compared to the control group, the peanut butter group did not demonstrate significant changes (p > 0.05) in sleep measures or subjective feelings of mood, focus, or alertness after consuming peanut butter for seven weeks. Therefore, peanut butter as a source of peanuts did not alter sleep quality or quantity in this group of firefighters.

Smartphone Applications (Apps) for Nutrition Education: A Qualitative Analysis of Outpatient Dietitian Perspectives

OBJECTIVE

To explore how outpatient dietitians select and use applications (apps) to support nutrition education.

METHODS

Qualitative analysis of 20 dietitians who participated in semistructured interviews investigating their app use and recommendation processes. Transcripts were analyzed using thematic analysis.

RESULTS

Four themes described how dietitians perceive apps for nutrition education: (1) nutrition education goals focus on long-term lifestyle behavior change while protecting patients' relationship with food, (2) attitudes toward tracking apps influence app selection, (3) dietitians differentiate among patients who will benefit from tracking vs information apps, and (4) barriers to optimal app use result in adaptations by dietitians.

CONCLUSIONS AND IMPLICATIONS

Barriers exist to optimal app use for nutrition education. However, accessible app design, app selection guides, and research expounding the effects of apps and their use by dietitians may improve how practitioners incorporate apps into nutrition education.

Validating Accuracy of an Internet-Based Application against USDA Computerized Nutrition Data System for Research on Essential Nutrients among Social-Ethnic Diets for the E-Health Era

Internet-based applications (apps) are rapidly developing in the e-Health era to assess the dietary intake of essential macro-and micro-nutrients for precision nutrition. We, therefore, validated the accuracy of an internet-based app against the Nutrition Data System for Research (NDSR), assessing these essential nutrients among various social-ethnic diet types. The agreement between the two measures using intraclass correlation coefficients was good (0.85) for total calories, but moderate for caloric ranges outside of <1000 (0.75) and >2000 (0.57); and good (>0.75) for most macro- (average: 0.85) and micro-nutrients (average: 0.83) except cobalamin (0.73) and calcium (0.51). The app underestimated nutrients that are associated with protein and fat (protein: −5.82%, fat: −12.78%, vitamin B12: −13.59%, methionine: −8.76%, zinc: −12.49%), while overestimated nutrients that are associated with carbohydrate (fiber: 6.7%, B9: 9.06%). Using artificial intelligence analytics, we confirmed the factors that could contribute to the differences between the two measures for various essential nutrients, and they included caloric ranges; the differences between the two measures for carbohydrates, protein, and fat; and diet types. For total calories, as an example, the source factors that contributed to the differences between the two measures included caloric range (<1000 versus others), fat, and protein; for cobalamin: protein, American, and Japanese diets; and for folate: caloric range (<1000 versus others), carbohydrate, and Italian diet. In the e-Health era, the internet-based app has the capacity to enhance precision nutrition. By identifying and integrating the effects of potential contributing factors in the algorithm of output readings, the accuracy of new app measures could be improved.

Nutrition-Related Mobile Apps in the French App Stores: Assessment of Functionality and Quality

BACKGROUND

The global burden of disease attributes 20% of deaths to poor nutrition. Although hundreds of nutrition-related mobile apps have been created, and these have been downloaded by millions of users, the effectiveness of these technologies on the adoption of healthy eating has had mixed.

OBJECTIVE

The aim of this study was to review which nutrition-related mobile apps are currently available on the French market and assess their quality.

METHODS

We screened apps on the Google Play Store and the French Apple App Store, from March 10 to 17, 2021, to identify those related to nutritional health. A shortlist of 15 apps was identified, and each was assessed using the French version of the Mobile App Rating Scale: 8 dietitians and nutritionists assessed 7 apps, and the remaining apps were randomly allocated to ensure 4 assessments per app. Intraclass correlation was used to evaluate interrater agreement. Means and standard deviations of scores for each section and each item were calculated.

RESULTS

The top scores for overall quality were obtained by Yazio - Régime et Calories (mean 3.84, SD 0.32), FeelEat (mean 3.71, SD 0.47), and Bonne App (mean 3.65, SD 0.09). Engagement scores ranged from a mean of 1.95 (SD 0.5) for iEatBetter: Journal alimentaire to a mean of 3.85 (SD 0.44) for FeelEat. Functionality scores ranged from a mean of 2.25 (SD 0.54) for Naor to a mean of 4.25 (SD 0.46) for Yazio. Aesthetics scores ranged from a mean of 2.17 (SD 0.34) for Naor to a mean of 3.88 (SD 0.47) for Yazio. Information scores ranged from a mean of 2.38 (SD 0.60) for iEatBetter to a mean of 3.73 (SD 0.29) for Yazio. Subjective quality scores ranged from a mean of 1.13 (SD 0.25) for iEatBetter to a mean of 2.28 (SD 0.88) for Compteur de calories FatSecret. Specificity scores ranged from a mean of 1.38 (SD 0.64) for iEatBetter to a mean of 3.50 (SD 0.91) for FeelEat. The app-specific score was always lower than the subjective quality score, which was always lower than the quality score, which was lower than the rating from the iOS or Android app stores.

CONCLUSIONS

Although prevention and information messages in apps regarding nutritional habits are not scientifically verified before marketing, we found that app quality was good. Subjective quality and specificity were associated with lower ratings. Further investigations are needed to assess whether information from these apps is consistent with recommendations and to determine the long-term impacts of these apps on users.

Evaluating the efficacy of mindfulness and acceptance-based treatment components for weight loss: Protocol for a multiphase optimization strategy trial

Behavioral weight loss treatment (BT) for individuals with overweight and obesity is effective but leaves room for improvement. Mindfulness and acceptance-based treatments may bolster weight loss outcomes; yet, little is known about the efficacy of the individual components or the combinations of components that are most effective in producing weight loss above and beyond standard BT strategies for weight loss. This protocol manuscript describes the use of a multiphase optimization strategy to evaluate the independent and combinatory efficacy of three mindfulness and acceptance-based components (mindful awareness, willingness, values). Using a 2 × 2 × 2 factorial design, participants (N = 288) will be randomized to one of eight conditions, each representing a combination of core MABT strategies in addition to foundational BT strategies. Assessments occur at baseline, mid-treatment (week 24 through 26), post-treatment, and at 6, 12, and 24-month follow-up. The primary aim is to elucidate the independent efficacy of each MABT component on weight loss above gold-standard BT. The secondary aims are to evaluate the independent effect of these components on calorie intake, physical activity, and overall quality of life; evaluate target engagement (i.e., the degree to which each treatment component affects proposed mechanisms of action); and evaluate the potential moderating effect of susceptibility to internal and external food cues on outcomes. The exploratory aim is to quantify any component interaction effects (which may be synergistic, fully additive, or partially additive).

Low Comparability of Nutrition-Related Mobile Apps against the Polish Reference Method-A Validity Study

Nutrition-related mobile applications (apps) are commonly used to provide information about the user’s dietary intake, however, limited research has been carried out to assess to what extent their results agree with those from the reference method (RM). The main aim of this study was to evaluate the agreement of popular nutrition-related apps with the Polish RM (Dieta 6.0). The dietary data from two days of dietary records previously obtained from adults (60 males and 60 females) were compared with values calculated in five selected apps (FatSecret, YAZIO, Fitatu, MyFitnessPal, and Dine4Fit). The selection of apps was performed between January and February 2021 and based on developed criteria (e.g., availability in the Polish language, access to the food composition database, and the number of downloads). The data was entered by experienced clinical dietitians and checked by one more researcher. The mean age of study participants was 41.7 ± 14.8. We observed that all the apps tended to overestimate the energy intake, however, when considering the macronutrient intake, over- and underestimation were observed. According to our assumed criterion (±5% as perfect agreement, ±10% as sufficient agreement), none of the apps can be recommended as a replacement for the reference method both for scientific as well as clinical use. According to the Bland-Altman analysis, the smallest bias was observed in Dine4Fit in relation to energy, protein, and fat intake (respectively: −23 kcal; −0.7 g, 3 g), however, a wide range between the upper and lower limits of agreement were reported. According to the carbohydrate intake, the lowest bias was observed when FatSecret and Fitatu were used. These results indicate that the leading nutrition-related apps present a critical issue in the assessment of energy and macronutrient intake. Therefore, the implementation of validation studies for quality assessment is crucial to develop apps with satisfying quality.

The Role of Eco-Apps in Encouraging Pro-Environmental Behavior of Young People Studying in Poland

Nowadays, protection of the natural environment is the fundamental duty and challenge of humanity. Adverse environmental changes make it necessary to encourage behaviors that will reduce our negative impact. Due to the development of media, information reaches consumers through various channels. New media, including mobile applications, are becoming increasingly popular. Their potential impact on young consumers cannot be overestimated as young people are able to modify their attitudes, behaviors and habits more easily than older ones. The main aim of this study was to recognize the use of eco-applications as a new source of information in the field of pro-environmental behavior of young people studying in Poland. The research objectives included the identification of pro-environmental behaviors most often declared by students, verifying their recognition and use of eco-applications, and determining the features of eco-app design expected by young users. The study involved the methods of desk research, in-depth interview and computer-assisted web interviewing (CAWI). The empirical material obtained from 772 students representing Generation Z underwent quantitative and qualitative analysis, which allowed for the verification the proposed hypotheses. The respondents most often declared pro-environmental behavior in the household context. As regards eco-apps, the respondents were most likely to recognize applications promoted via traditional media. The main feature expected of eco-app design was ease of use, which does not mean that users expected the app to be in Polish, as this criterion was relatively low rated. The Mann-Whitney test and the Kruskal-Wallis test revealed relationships between such variables as gender, place of residence or income and pro-environmental behavior, the use of selected eco-apps and the expected features of eco-app design.