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The Validity, Time Burden, and User Satisfaction of the FoodImage™ Smartphone App for Food Waste Measurement Versus Diaries: A Randomized Crossover Trial.

ABSTRACT: The FoodImage™ smartphone app transmits to researchers users' photographs of food selection and food waste, and includes user-tagged information about waste reasons and destination. Twenty-four participants were trained to record food waste using FoodImage, food waste diaries requiring visual estimation of waste quantities, and diaries requiring scale weights. Participants used each method during three staged food-waste scenarios (food preparation, eating, and clean-out) in a randomized crossover trial. Two participants had extreme values for the weighed diary method; therefore, accuracy results are reported with and without these two participants' data. Error was calculated as waste estimated with the experimental method minus directly weighed waste. Mean absolute error from FoodImage was significantly smaller than or equal to the error from both diary methods in each scenario. Furthermore, the mean values from FoodImage were equivalent to directly weighed values in two out of the three tasks; while weighed diaries were equivalent in two tasks only when the two participants with extreme values were removed. Visually estimated diaries were equivalent for only one task. All 24 participants preferred FoodImage to diaries and all rated FoodImage as less time consuming. Over one week, FoodImage would require ~24 fewer minutes of users' time to record all data. Unlike food waste diaries, FoodImage also transmits data to researchers in real-time and provides detailed data on food selection and intake. ClinicalTrials.gov Identifier: NCT03309306.

SUBMITTER: Roe BE

PROVIDER: S-EPMC7409719 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThere is strong evidence suggesting that higher levels of cardiorespiratory fitness (CRF) are associated with a healthier metabolic profile, and that CRF can serve as a powerful predictor of morbidity and mortality. In this context, a smartphone app based on the 2-km walk test (UKK test) would provide the possibility to assess CRF remotely in individuals geographically distributed around a country or continent, and even between continents, with minimal equipment and low costs.ObjectiveThe overall aim of this study was to evaluate the validity and reliability of 2kmFIT-App developed for Android and iOS mobile operating systems to estimate maximum oxygen consumption (VO2max) as an indicator of CRF. The specific aims of the study were to determine the validity of 2kmFIT-App to track distance and calculate heart rate (HR).MethodsTwenty participants were included for field-testing validation and reliability analysis. The participants completed the UKK test twice using 2kmFIT-App. Distance and HR were measured with the app as well as with accurate methods, and VO2max was estimated using the UKK test equation.ResultsThe validity results showed the following mean differences (app minus criterion): distance (-70.40, SD 51.47 meters), time (-0.59, SD 0.45 minutes), HR (-16.75, SD 9.96 beats/minute), and VO2max (3.59, SD 2.01 ml/kg/min). There was moderate validity found for HR (intraclass correlation coefficient [ICC] 0.731, 95% CI -0.211 to 0.942) and good validity found for VO2max (ICC 0.878, 95% CI -0.125 to 0.972). The reliability results showed the following mean differences (retest minus test): app distance (25.99, SD 43.21 meters), app time (-0.15, SD 0.94 seconds), pace (-0.18, SD 0.33 min/km), app HR (-4.5, 13.44 beats/minute), and app VO2max (0.92, SD 3.04 ml/kg/min). There was good reliability for app HR (ICC 0.897, 95% CI 0.742-0.959) and excellent validity for app VO2max (ICC 0.932, 95% CI 0.830-0.973). All of these findings were observed when using the app with an Android operating system, whereas validity was poor when the app was used with iOS.ConclusionsThis study shows that 2kmFIT-App is a new, scientifically valid and reliable tool able to objectively and remotely estimate CRF, HR, and distance with an Android but not iOS mobile operating system. However, certain limitations such as the time required by 2kmFIT-App to calculate HR or the temperature environment should be considered when using the app.

Project description:BackgroundGlobal sustainability and individual health need coordinated attention. While individuals are recommended a healthy diet to reduce the burden of noncommunicable diseases, global attention to natural resource conservation is also needed. The latter specifically means effective measures to reduce food waste.ObjectiveThis pilot study evaluates the experiences of students and effect from using smartphone apps designed to reduce food waste on personal healthy eating, financial expenses, and food waste.MethodsA total of 6 students from different study programs (mean age 24.7, SD 2.9) were recruited to evaluate 2 different apps designed to reduce food waste and to register food consumption, food waste, and financial food expenses before and after the app trials. The apps evaluated were the commercially available TotalCtrl Home and Too-Good-To-Go. Results were analyzed by mixed methods, comprising statistical analyses for quantifiable data and thematic analyses for qualitative data. The apps were used separately in random order, each for 1 month. Primary outcome was user expectations to and experiences from the use of the apps, which were obtained by semistructured interviews. Secondary outcomes were changes in food waste volume, financial food expenses, and healthy eating. While information on food waste and food expenses was obtained by weighing food waste and registering food costs for 2 weeks before and after app trials, scores for consuming healthy diets were calculated from registered food records by scoring criteria matched to national recommendations for healthy eating.ResultsAwareness on food waste increased after app trials, but experiences with apps pointed toward several potential for technical and content improvements. The students reported that there were too many manual operations in the apps to induce permanent use (TotalCtrl Home), that services seemed more concerned about the producers' interests than the individual's needs (Too-Good-To-Go), and that they missed a composite app that included functions to promote healthy eating and overview of budget and expenses as well as of food waste (both apps). Use of apps designed to reduce food waste and personal costs and to improve healthy eating did not result in any measurable effects, that is, no change in food waste (mean change 0.81, SD 1.5 kg; P=.13), healthy eating (mean change -0.24, SD 0.43; P=.24), or personal food expenses (mean change 47.5 NOK or US $4.8, SD 416.9 NOK or US $42.5; P=.39).ConclusionsApps may aid in increased awareness of food waste at the producer and consumer levels. Large-scale studies with longer duration are needed to see if apps may induce measurable changes in food waste, healthy eating, and financial expenses.

Project description:BackgroundAccurate dietary assessment is needed in studies that include analysis of nutritional intake. Image-based dietary assessment apps have gained in popularity for assessing diet, which may ease researcher and participant burden compared to traditional pen-to-paper methods. However, few studies report the validity of these apps for use in research. Keenoa is a smartphone image-based dietary assessment app that recognizes and identifies food items using artificial intelligence and permits real-time editing of food journals.ObjectiveThis study aimed to assess the relative validity of an image-based dietary assessment app - Keenoa - against a 3-day food diary (3DFD) and to test its usability in a sample of healthy Canadian adults.MethodsWe recruited 102 participants to complete two 3-day food records. For 2 weeks, on 2 non-consecutive days and 1 weekend day, in random order, participants completed a traditional pen-to-paper 3DFD and the Keenoa app. At the end of the study, participants completed the System Usability Scale. The nutrient analyses of the 3DFD and Keenoa data before (Keenoa-participant) and after they were reviewed by dietitians (Keenoa-dietitian) were analyzed using analysis of variance. Multiple tests, including the Pearson coefficient, cross-classification, kappa score, % difference, paired t test, and Bland-Altman test, were performed to analyze the validity of Keenoa (Keenoa-dietitian).ResultsThe study was completed by 72 subjects. Most variables were significantly different between Keenoa-participant and Keenoa-dietitian (P<.05) except for energy, protein, carbohydrates, fiber, vitamin B1, vitamin B12, vitamin C, vitamin D, and potassium. Significant differences in total energy, protein, carbohydrates, % fat, saturated fatty acids, iron, and potassium were found between the 3DFD and Keenoa-dietitian data (P<.05). The Pearson correlation coefficients between the Keenoa-dietitian and 3DFD ranged from .04 to .51. Differences between the mean intakes assessed by the 3DFD and Keenoa-dietitian were within 10% except for vitamin D (misclassification rate=33.8%). The majority of nutrients were within an acceptable range of agreement in the Bland-Altman analysis; no agreements were seen for total energy, protein, carbohydrates, fat (%), saturated fatty acids, iron, potassium, and sodium (P<.05). According to the System Usability Scale, 34.2% of the participants preferred using Keenoa, while 9.6% preferred the 3DFD.ConclusionsThe Keenoa app provides acceptable relative validity for some nutrients compared to the 3DFD. However, the average intake of some nutrients, including energy, protein, carbohydrates, % fat, saturated fatty acids, and iron, differed from the average obtained using the 3DFD. These findings highlight the importance of verifying data entries of participants before proceeding with nutrient analysis. Overall, Keenoa showed better validity at the group level than the individual level, suggesting it can be used when focusing on the dietary intake of the general population. Further research is recommended with larger sample sizes and objective dietary assessment approaches.

Project description:BACKGROUND:Smartphone apps for heart rate variability (HRV) measurement have been extensively developed in the last decade. However, ultra-short-term HRV recordings taken by wearable devices have not been examined. OBJECTIVE:The aims of this study were the following: (1) to compare the validity and reliability of ultra-short-term and short-term HRV time-domain and frequency-domain variables in a novel smartphone app, Pulse Express Pro (PEP), and (2) to determine the agreement of HRV assessments between an electrocardiogram (ECG) and PEP. METHODS:In total, 60 healthy adults were recruited to participate in this study (mean age 22.3 years [SD 3.0 years], mean height 168.4 cm [SD 8.0 cm], mean body weight 64.2 kg [SD 11.5 kg]). A 5-minute resting HRV measurement was recorded via ECG and PEP in a sitting position. Standard deviation of normal R-R interval (SDNN), root mean square of successive R-R interval (RMSSD), proportion of NN50 divided by the total number of RR intervals (pNN50), normalized very-low-frequency power (nVLF), normalized low-frequency power (nLF), and normalized high-frequency power (nHF) were analyzed within 9 time segments of HRV recordings: 0-1 minute, 1-2 minutes, 2-3 minutes, 3-4 minutes, 4-5 minutes, 0-2 minutes, 0-3 minutes, 0-4 minutes, and 0-5 minutes (standard). Standardized differences (ES), intraclass correlation coefficients (ICC), and the Spearman product-moment correlation were used to compare the validity and reliability of each time segment to the standard measurement (0-5 minutes). Limits of agreement were assessed by using Bland-Altman plot analysis. RESULTS:Compared to standard measures in both ECG and PEP, pNN50, SDNN, and RMSSD variables showed trivial ES (<0.2) and very large to nearly perfect ICC and Spearman correlation coefficient values in all time segments (>0.8). The nVLF, nLF, and nHF demonstrated a variation of ES (from trivial to small effects, 0.01-0.40), ICC (from moderate to nearly perfect, 0.39-0.96), and Spearman correlation coefficient values (from moderate to nearly perfect, 0.40-0.96). Furthermore, the Bland-Altman plots showed relatively narrow values of mean difference between the ECG and PEP after consecutive 1-minute recordings for SDNN, RMSSD, and pNN50. Acceptable limits of agreement were found after consecutive 3-minute recordings for nLF and nHF. CONCLUSIONS:Using the PEP app to facilitate a 1-minute ultra-short-term recording is suggested for time-domain HRV indices (SDNN, RMSSD, and pNN50) to interpret autonomic functions during stabilization. When using frequency-domain HRV indices (nLF and nHF) via the PEP app, a recording of at least 3 minutes is needed for accurate measurement.

Project description:BackgroundPostdischarge interventions are limited for patients with acute coronary syndrome (ACS) due to few scheduled visits to outpatient clinics and the need to travel from remote areas. Smartphones have become viable lifestyle technology to deliver home-based educational and health interventions.ObjectiveThe aim of this study was to develop a smartphone-based intervention for providing postdischarge support to patients with ACS.MethodsThe content of Mobile Technology-Enabled Rehabilitation for Patients with ACS (MoTER-ACS) was derived from a series of small studies, termed prestudy surveys, conducted in 2017. The prestudy surveys were conducted in Prince Charles Hospital, Queensland, Australia, and consisted of questionnaires among a convenience sample of patients with ACS (n=30), a focus group discussion with health care professionals (n=10), and an online survey among cardiologists (n=15). Responses from the patient survey identified educational topics of MoTER-ACS. The focus group with health care professionals assisted with identifying educational materials, health monitoring, and self-management interventions. Based on the results of the cardiologists' survey, monitoring of symptoms related to heart failure exacerbation was considered as a weekly diary.ResultsThe MoTER-ACS app covers multimedia educational materials to adopt a healthy lifestyle and includes user-friendly tools to monitor physiological and health parameters such as blood pressure, weight, and pain, assisting patients in self-managing their condition. A web portal that is linked to the data from the smartphone app is available to clinicians to regularly access patients' data and provide support.ConclusionsThe MoTER-ACS platform extends the capabilities of previous mobile health platforms by providing a home-based educational and self-management intervention for patients with ACS following discharge from the hospital. The MoTER-ACS intervention narrows the gap between existing hospital-based programs and home-based interventions by complementing the postdischarge program for patients with ACS.

Project description:BackgroundUnderstanding how users engage with electronic screening and brief intervention (eSBI) is a critical research objective to improve effectiveness of app-based interventions to reduce harmful alcohol consumption. Although quantitative measures of engagement provide a strong indicator of how the user engages with an app at the group level, they do not elucidate finer-grained details of how apps function from an individual, experiential perspective and why, or how, users engage with an intervention in a particular manner.ObjectiveThe aim of this study was to (1) understand why and how participants engaged with the BRANCH app, (2) explore facilitators and barriers to engagement with app features, (3) explore how the BRANCH app impacted drinking behavior, (4) use these data to identify typologies of users of the BRANCH app in terms of engagement behaviors, and (5) identify future eSBI app design implications.MethodsIn total, 20 one-to-one semistructured telephone interviews were conducted with participants recruited from a randomized controlled trial, which evaluated the effectiveness of engagement-promoting strategies in the BRANCH app targeting harmful drinking in young adults (aged 18-30 years). The topic guide explored users' current engagement levels with existing health promotion apps, their views toward the effectiveness of such apps, and what they liked and disliked about BRANCH, specifically focusing on how they engaged with the app. Framework analysis was used to develop typologies of user engagement.ResultsThe study identified 3 typologies of engagers. Trackers were defined by their motivations to use health-tracking apps to monitor and understand quantified self-data. They did not have intentions necessarily to cut down and predominantly used only the drinking diary. Cut-downers were motivated to use the app because they wanted to reduce their alcohol consumption Unlike Trackers, they did not use a range of different health apps daily, but saw the BRANCH app as an opportunity to test out a different method of trying to cut down their alcohol use. This typology used more features than Trackers, such as the goal setting function. Noncommitters were characterized as a group of users who were initially enthusiastic about using the app; however, this enthusiasm quickly waned and they gained no benefit from it.ConclusionsThis was the first study to identify typologies of user engagement with eSBI apps. Although in need of replication, it provides a first step in understanding independent categories of eSBI users, who may benefit from apps tailored to a user's typology or motivation. It also provides new evidence to suggest that apps may be used more effectively as a tool to raise awareness of drinking, instead of reducing alcohol use, and be a step in the care pathway, identifying at-risk individuals and signposting them to more intensive treatment.Trial registrationInternational Standard Randomised Controlled Trial Number ISRCTN70980706; http://www.isrctn.com /ISRCTN70980706 (Archived by WebCite at http://www.webcitation.org/73vfDXYEZ).

Dataset Information

The Validity, Time Burden, and User Satisfaction of the FoodImage™ Smartphone App for Food Waste Measurement Versus Diaries: A Randomized Crossover Trial.

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